About the Team

The Analytics team is looking for Data Analysts and Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our logistics platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash.

About the Role

Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. It is NOT just about building Machine Learning models and putting them into production. This is a rare operational and actionable data-driven experience. 

We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you!

You're excited about this opportunity because you will…

• Be a first-class thought partner to our product, business, finance and executive teams and help them make decisions on what’s next for DoorDash
• Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business
• Build full-cycle analytics experiments, reports, and dashboards using SQL, Python, R, or other scripting and statistical tools
• Produce recommendations and use statistical techniques and hypothesis testing and other experimentation techniques to validate your findings
• Provide insights to enable our cross-functional team to understand marketplace dynamics, user behaviours, and long-term trends
• Identify and measure levers to help move essential metrics and make recommendations
• Possess excellent stakeholder management skills, know how to effectively collaborate well with strategy, operations, product, finance and engineering and set priorities
• Be excited to travel to meet with business partners and the teams in each market

We're excited about you because… 

• 3+ years of experience in data analytics, consulting, or related role
• The insight to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way
• The determination to initiate and lead/own strategic projects to completion with a cross-functional team
• Experience working with experimentation techniques (A/B testing, Causal Inference) and interpreting hypothesis testing
• Proficiency in at least one programming language (Python, R,...)
• Expertise with SQL queries, ETLs, etc… 
• Proficiency in one or more analytics & visualization tools
• Experience building and training statistical and machine learning models (classifiers, regression models...)

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

The Growth Tech Alliance's goal is to enable HelloFresh to drive smarter marketing through AI-powered automation, intelligent systems, and advanced optimization. We've pioneered cutting-edge approaches to programmatic campaign optimization using state-of-the-art AI/ML technologies and are now scaling these capabilities across our global marketing operations. Our team’s key responsibilities include designing, building, maintaining autonomous decision-making systems, advanced ML models for marketing optimization, and real-time intelligence that drives measurable business impact. We work at the intersection of modern AI architectures, deep statistical modelling, and enterprise-scale ML operations.

S'more about the team

As a Senior Data Scientist in AdTech, you will design, build, and deploy production-grade machine learning models that drive significant marketing ROI. You will provide critical expertise in advancing our intelligent marketing optimization systems, focusing on the entire ML lifecycle from data preprocessing and feature engineering to large-scale deployment and performance monitoring. By translating complex marketing challenges into robust production systems, you will ensure our AI-driven capabilities deliver measurable business impact and enhanced efficiency at a  global scale

Lettuce share what this role will be responsible for

• Develop, build, and iterate on advanced machine learning models across core adtech domains to optimize marketing performance and contribute to the orchestration of highly efficient marketing workflows.
• Design and implement ML models for Media Optimization, and contribute to their operationalization into high-impact production systems.
• Contribute to Creative Automation efforts by building and enhancing predictive AI models to guide our global production studios.
• Design and build ML models for Value Optimization to intelligently isolate high-value customers.
• Adhere to and contribute to the team's ML operations (MLOps) practices, focusing on experiment tracking, system observability, and model reliability in production.
• Rapidly prototype innovative machine learning solutions, including Gen AI-forward approaches, and integrate them into our existing, orchestrated multi-agent systems to enable complex autonomous workflows.
• Collaborate closely with Product, Engineering, and Marketing to identify high-impact programmatic automation opportunities and execute robust A/B testing and experimentation designs for models in high-noise environments.
• All other duties, as assigned

Sound a-peeling? Here's what we're looking for

• MSc or equivalent experience in a quantitative discipline with proven experience building and deploying AI/ML systems from prototype to production at scale
• Expert proficiency in Python, PySpark, and SQL, hands-on experience with cloud environments (GCP, AWS, or Azure), and practical experience with modern machine learning frameworks such as HuggingFace, TensorFlow or similar.
• Expertise in applied machine learning relevant to AdTech, including predictive modeling, optimization algorithms, and modern LLM capabilities preferred.
• Proven experience tackling complex marketing data problems, such as algorithmic budget pacing, LTV prediction pipelines, or AI-driven media optimization systems.
• Strong foundation in statistical analysis and experimentation, with practical experience designing A/B tests to validate the incremental business impact of algorithmic systems
• Demonstrated ability to effectively communicate intricate analytical findings to diverse audiences, bridging the gap between deep technical implementation and core business KPIs
• Track record of building production ML systems with robust practices, demonstrating a bias for action and extreme ownership, treating the business outcomes of your algorithms with a true Founder Mentality
• Experience with programmatic advertising ecosystems, marketing analytics, and the operational aspects of running performance-critical ML models in high-traffic environments

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Fraud Data Science team safeguards Robinhood and its customers by detecting and preventing fraud and abuse across our platform. We leverage machine learning and analytics to combat malicious behavior in real time, supporting a safe and trusted experience for all users. Our work has a direct impact on customer security, company risk posture, and regulatory compliance.

As a Senior Data Scientist on the Fraud team, you will own the design and deployment of ML solutions that proactively surface suspicious activity, reduce financial loss, and improve fraud detection precision. You’ll collaborate closely with engineering, product, risk, and compliance partners to influence system architecture, shape policy through data, and enhance the safety and integrity of our platform.

This role is based in our Menlo Park office, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

What you’ll do

• Design and deploy fraud detection models to protect Robinhood users and assets in real time
• Analyze behavioral data to uncover emerging fraud vectors and support rapid incident response
• Develop robust data pipelines and monitoring systems to ensure model accuracy and reliability
• Partner with engineering and product teams to implement safeguards and user-facing features
• Guide experimentation strategy and contribute to long-term fraud prevention roadmap

What you bring

• 5+ years of experience in data science or applied ML, with a focus on fraud detection or risk mitigation
• Advanced proficiency in Python and SQL; experience with ML frameworks like XGBoost, LightGBM, or TensorFlow
• Strong statistical acumen with experience in anomaly detection, pattern recognition, and A/B testing
• Excellent communication skills and ability to influence decision-making across technical and non-technical audiences
• A collaborative mindset and proactive approach to navigating ambiguity in fast-paced environments

What we offer

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, recommending and implementing technical solutions, designing experiments, shaping team priorities, and measuring the impact of new features.

The Verticals team encompasses 3 critical and unique products / marketplaces within Lyft: airports, scheduled rides, and events. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experiences and have unique considerations and dynamics. Scheduled rides allow riders to book a ride in advance with high reliability, and enable drivers to add structure to their work schedule. Lastly, events such as concerts or sporting games require similar considerations of special operations to ensure a seamless experience for both riders and drivers. 

As a Data Scientist on the Verticals team, you will collaborate with engineering, product, design, and operations to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as:

• How can we efficiently match riders and drivers together in these unique marketplaces, to minimize ETAs and improve the driver experience? 
• Are we able to forecast ride demand and implement driver guidance to ensure riders can rely on Lyft for an event ride?
• What is the most helpful way to display ride information to drivers so they can make informed decisions?
• What rider segments should we target with ride incentives to grow our marketshare for these verticals? 

Responsibilities:

• Construct and fit statistical or optimization models to make production decisions such as changes to how we match riders and drivers; focusing on model proposal and offline model development 
• Leverage data and analytic frameworks to identify opportunities for growth and efficiency, recommending technical solutions to drive business impact 
• Design and analyze online experiments, including communicating results, acting on launch decisions, and recommending next steps based on learnings
• Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action
• Develop analytical frameworks to monitor business and product performance, leveraging experiments and causal inference
• Establish metrics that measure the health of our products, the business, as well as the driver experience

Experience 

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years of industry experience in a data science, analytics, or management consulting role
• Proficiency in SQL and Python
• Ability to perform technical experiments, including user split, time split, and region split
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Ability to manage, influence, negotiate, and inspire others in a fast-moving environment
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in mapping, including:

• How do we improve the quality of our map data in order to improve our recommendations?
• How do we benchmark and measure the success of our services?
• How do we validate features of the real world that affect our routing algorithms?
• Are we meeting our travel estimation promises to our customers?

Responsibilities

• Leverage data and analytic frameworks to identify opportunities for growth and efficiency
• Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals
• Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty
• Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope
• Design and analyze online experiments; communicate results and act on launch decisions
• Establish metrics that measure the health of our products, as well as rider and driver experience
• Identify and drive impact and alignment, shaping product and business strategy through data-centric presentations 
• Contribute to the Science community (hiring, onboarding, documentation, knowledge-sharing, tooling improvements), helping make Decision Science at Lyft more effective and scalable

Experiences

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years experience in a data science role or analytics role
• Demonstrated ability to own multi-project analytical scopes with ambiguous problem definitions and cross-functional integration
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency in SQL - able to write structured and efficient queries on large data sets
• Experience in programming, especially with data science and visualization libraries in Python or R, and machine learning libraries such as PyTorch, TensorFlow, Keras
• Experience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholders
• Strong communication, critical thinking, and prioritization skills, including the ability to challenge assumptions, propose alternatives, and balance short-term vs. long-term tradeoffs
• Experience in applying machine learning techniques is a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
• Expertise in metric design, causal analysis, behavioral analytics, decision frameworks and measurement strategy is a plus
• Experience working with ETL pipelines a plus

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is $108,000 - $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We are hiring motivated experts in each of these fields. We're looking for someone who is passionate about solving mathematical problems with data, and are excited about working in a fast-paced, innovative and collegial environment.

You will report into a Science Manager.

Responsibilities:

• Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
• Perform exploratory data analysis to gain a deeper understanding of the problem
• Construct and fit statistical, machine learning, or optimization models
• Write production modeling code; collaborate with Software Engineers to implement algorithms in production
• Design and run both simulated and live traffic experiments
• Analyze experimental and observational data; communicate findings; facilitate launch decisions

Experience:

• Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields
• 2+ years professional experience in a technology companies
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency with Python, or another interpreted programming language like R or Matlab
• Willingness to collaborate and communicate with others to solve a problem

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Safety & Customer Care (SCC) organization manages over 1.7 million monthly customer interactions and is responsible for ensuring the trust and safety of our riders and drivers. We work every day to build a trusted community, foster safe interactions, manage risky situations, and deliver best-in-class support. As part of this team, you will play a critical role in making transportation safer for all.

We are looking for an experienced and highly motivated Data Scientist to join the Community Safety Data team and lead key initiatives that enhance the safety of Lyft’s community. You’ll work cross-functionally with product management, engineering, design, legal, research, and operations teams to build impactful safety features, models, and systems. This high-impact role requires deep customer empathy, insatiable curiosity to uncover platform risks; and competencies to explore large datasets, develop statistical models, and design data-driven strategies for products that provide safe and engaging experiences for customers.

You’ll report to the Director of Data Science for the SCC org.

Responsibilities:

• Leverage data and analytical frameworks to identify opportunities for improving community trust and safety
• Partner with product managers, engineers, designers, marketers, and operators to translate insights into scalable, safety-forward decisions
• Design and analyze online experiments; interpret and communicate results to influence product launch decisions
• Build and monitor key metrics that reflect rider and driver safety, product health, and policy compliance
• Develop rigorous measurement strategies to evaluate the effectiveness of safety features, interventions, and detection systems
• Drive proactive risk identification and continuous improvement through analysis, experimentation, and iteration
• Mentored junior data scientists by providing guidance, feedback, and support to accelerate their technical and soft skill growth and impact.

Experience:

• Degree in a quantitative field such as Statistics, Economics, Applied Mathematics, Operations Research, or Engineering (advanced degrees preferred), or equivalent professional experience
• 3+ years of industry experience in data science or product analytics roles
• Proficiency in SQL with ability to write efficient queries on large, complex datasets
• Experience programming in Python or R, especially for data analysis, visualization, and modeling
• Strong foundation in statistical analysis and experimentation, including A/B testing design and/or Causal Inference techniques
• Excellent written and verbal communication skills with ability to influence cross-functional partners and executives, and translate data into compelling stories
• Self-starter with a curious mindset and a strong sense of ownership
• Ability to combine business intuition with the application of advanced solutions
• A passion for keeping up with the latest ongoings in Data Science and Machine Learning communities, and an obsession for data quality
• Prior experience in Trust & Safety, or Platform Integrity domains is a plus

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108000-$135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Understanding and improving how we deliver and optimize ads to Pinners is fundamental to Pinterest’s long-term success.  We’re looking for a data scientist to join our team in pushing the boundaries in ads delivery and optimization. You will be a key member of an organization of talented data scientists innovating on ads delivery.

What you’ll do:

We are looking for an experienced and highly capable Data Scientist to help us drive step function improvements in our ads delivery at Pinterest. In this role, you will:

• Strategy: Evolve our strategy by working closely with product and engineering leaders to build on past learnings and shape our platform's future.
• Experimentation: Improve our experimentation capabilities and tools for assessing our ad delivery system, advise on best practices, identify flaws, and build tools and frameworks for experiment analysis.
• Leadership: Lead and mentor peers, improving team output through continuous, candid feedback that recognizes strengths and identifies areas for growth. Be a technical leader for junior data scientists based in the Toronto office.
• Communication: Clearly and concisely communicate complex analytical findings and insights to stakeholders with varying technical backgrounds.
• Continuous Learning: Stay informed on the latest developments in data science, causal inference, and advertising technology to drive innovation.
• Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches)
• Leverage AI to synthesize information (summarize, distill themes) and automate repeatable tasks (documentation, reporting, QA checks)

What we’re looking for:

• 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data, preferred to have working knowledge of ads delivery and optimization systems.
• Proven ability to apply scientific methods to solve real-world problems on web-scale data
• Expertise in SQL and Python
• Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions
• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams 
• Experience leading key technical projects and substantially influencing the scope and output of others
• Experience in digital ad delivery stacks preferred
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
• Bachelor’s or Master’s degree in a relevant field such as Data Science, or equivalent experience

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement:

• This position is not eligible for relocation.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration 1-2 times per half and therefore can be situated anywhere in Ontario. 

#LI-CH1 #LI-HYBRID

We are looking for a Senior Data Scientist. You will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and uplevel our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world.

What you’ll do

• Develop best practices for instrumentation and experimentation and communicate those to product engineering teams to help us fulfill our mission - to bring everyone the inspiration to create a life they love.
• Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners.
• Build and prototype analysis pipelines iteratively to provide insights at scale while developing comprehensive knowledge of data structures and metrics, advocating for changes where needed for product development.
• Work cross-functionally to build and communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest.
• Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches).
• Leverage AI to synthesize information (summarize, distill themes) and automate repeatable tasks (documentation, reporting, QA checks).

What we’re looking for

• • 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
  • Extensive experience solving analytical problems using quantitative approaches including in the fields of Statistics, Machine Learning, Forecasting, Econometrics or other related fields.
  • Experience solving problems within digital advertising is preferred.
  • Familiarity with online experimentation and its pitfalls.
  • A scientifically and statistically rigorous approach to analysis and data.  You rely on statistically valid approaches to problems and have a well-tuned sense of skepticism, attention to detail and commitment to high-quality, results-oriented output.
  • Ability to manipulate large data sets with high dimensionality and complexity; fluency in SQL (or other database languages) and a scripting language (Python or R).
  • Excellent communication skills and ability to explain learnings to both technical and non-technical partners, including Product and Machine Learning teams.
  • A team player who’s able to partner with cross-functional leadership to quickly turn insights into actions.
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
  • Bachelor’s or Master’s degree in a relevant field such as Data Science, or equivalent experience.

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

This role will need to be in the office for in-person collaboration 1-2 times per half and therefore can be situated anywhere in Ontario. 

#LI-HYBRID

#LI-CH1

Upwork Inc.’s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond.

Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. Learn more about the Upwork Marketplace at Upwork.com and follow us on LinkedIn, Facebook, Instagram, TikTok, and X; and learn more about Lifted at Go-Lifted and follow on LinkedIn.

Sr. Lead AI Research Scientist, AI Evaluation and Reliability

The AI Foundations team leads core research and development across the training, evaluation, and deployment of AI systems that power Uma, Upwork’s flagship AI model, and other customer-facing generative AI capabilities. As a Sr. Lead AI Research Scientist focused on AI Evaluation and Reliability, you will drive high-impact research initiatives that improve the trustworthiness, robustness, and real-world performance of AI systems operating at marketplace scale.

At the Sr. Lead level, this role combines deep technical expertise with cross-functional leadership. You will identify and lead research efforts that address systemic reliability challenges, partner closely with engineering and product teams to translate research into production outcomes, and help shape how Upwork evaluates AI performance in real work scenarios. Your work will support AI systems embedded in retrieval-based workflows, agentic architectures, and human plus AI collaboration patterns, while contributing to Upwork’s broader AI research strategy and external presence.

Responsibilities:

• Lead applied research initiatives focused on AI evaluation, reliability, and robustness, defining success metrics tied to customer impact and production readiness.

• Design and validate methods to measure and mitigate AI reliability risks, including uncertainty estimation, hallucination detection, and identification of model failure modes.

• Partner cross-functionally with engineering, data science, and product teams to integrate research outcomes into customer-facing AI systems and workflows.

• Own research projects end to end, from problem framing and hypothesis development through experimentation, prototyping, and synthesis of results.

• Influence technical direction across teams by surfacing insights, proposing scalable solutions, and aligning stakeholders on priorities and tradeoffs.

• Mentor researchers and engineers through technical guidance, feedback, and collaborative leadership on shared initiatives.

• Contribute to Upwork’s external research footprint through publications, presentations, and engagement with the broader AI research community.

What it takes to catch our eye:

• Proven experience leading applied AI research that balances scientific rigor with real-world deployment constraints and business impact.

• A strong record of research contribution through publications, internal innovation, or demonstrable influence on production AI systems.

• Deep proficiency with Python and modern deep learning frameworks such as PyTorch, with hands-on experience evaluating and improving large-scale models.

• An adaptive approach to integrating AI tools into research and development workflows to accelerate experimentation, improve evaluation quality, and share best practices with others.

• A collaborative, growth-oriented mindset with the ability to mentor peers, communicate complex ideas clearly, and thrive in a fast-evolving, bottom-up environment.
  
  

Come change how the world works.

Upwork is establishing an operational hub in Toronto, Canada. The new office is expected to be fully operational by Q4 2026. This role will require 3 days in office once we have an office open.

This position will initially be employed through a partner to ensure a seamless hiring process while we establish the hub. Once the hub is established, there may be opportunities to transition to employment with Upwork, depending on business needs and other requirements. While employed by the partner, you’ll work as part of Upwork’s team, with access to our resources, culture, and growth opportunities.

Our partner will offer competitive benefits. When Upwork’s hub is established, we will be excited to offer employment and benefits directly as business needs require. 

Upwork is committed to building a diverse, inclusive, and equitable workforce. Employment decisions are made without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or any other status protected by applicable law.

We use BrightHire, an AI-enabled tool, to record interviews and summarize interview transcripts. The tool allows the interviewer to focus on the discussion and does not score or evaluate candidates or make recommendations. The interview transcripts are reviewed, and decisions are only made by humans. Candidates who prefer not to have their interview recorded through BrightHire can opt out when the interview is scheduled.

To learn more about how Upwork processes and protects your personal information as part of the application process, please review our Global Job Applicant Privacy Notice and the Applicant Privacy Addendum (Canada).

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Data Scientist Intern who can help us discover the value out of our rich and large datasets. Our ideal team member will have the mathematical and statistical expertise you’d expect, but a natural curiosity and creative mind that’s not so easy to find. As you mine, interpret and clean our data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the ultimate goal of realizing the data’s full potential. You will join a team of data specialists, but will “slice and dice” data using your own methods, creating new visions for the future. If you love technology and are keen to join an industry leader — we would love to hear from you!

What you'll do:

As a Data Scientist Intern, you will be a crucial part of producing innovative analytics from Geotab’s big data environment. We believe that there is collective value in the massive amount of data arising from all of our sensors across the globe. And most importantly, we believe this data can be used to improve safety, infrastructure, and productivity for our customers. You will work with our team of data scientists and engineers who have curated our data repository and have created a series of near real-time and historical datasets. You will leverage data mining techniques, Machine Learning, Deep Learning, Neural Networks and other Artificial Intelligence and statistical analysis tools to build models and high-quality prediction systems to help our customers make informed and smarter decisions. You will work closely with Data Analysts, Data Engineers, Professional Services, Data Privacy & Governance, firmware as well as other internal departments such as Software Development and Solutions Engineering to achieve these objectives.

The opportunity:

• 8+ month work-term beginning September 2026.
• Full-time, paid internship: Monday - Friday, 37.5hrs/week.
• Your first week at Geotab begins with 'GEO Launch' - a one-week Employee Orientation. Click here to learn more!
• Learn more about the Geotab Campus Program here.
• This posting is for an existing vacancy.

How you'll make an impact:

• The primary objective of this internship is to develop a "Reasoning & Automation" solution that evolves Geotab Ace into a fully integrated, context-aware assistant. Key goals include:
  • Multi-Modal Ingestion: Implement a multi-modal ingestion layer (leveraging technologies like Google's LiveAPI) capable of processing screen content, audio, and text simultaneously to establish real-time user context.
  • Contextual Enrichment: Develop mechanisms to automatically enrich user prompts with environmental state (e.g., current page URL, visible data charts), eliminating the need for users to manually explain their context.
  • Proactive Assistance & Navigation: Extend the reasoning capabilities of the agent to not only answer data queries but also guide users through complex workflows ("Where do I go to...") and offer proactive support.
  • Optimization of RAG & SQL Generation: Continue to refine the underlying RAG architecture and "text-to-SQL" generation for Google BigQuery to ensure the answers provided are accurate, safe, and efficient.

What you'll bring to the role:

We are a Canadian leader in digital automotive solutions. Our flagship brands — AutoTrader.ca, AutoSync, Dealertrack Canada and CMS — help Canadians buy, sell, and finance vehicles with confidence. 

AutoTrader.ca is Canada’s largest automotive marketplace, with over 25 million monthly visits. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond.

What's in it for you:

We understand that there is life at work and life outside of work. Here are a few benefits we all benefit from that support us to be our creative best. 

• Gym discounts 

• Employee and Family Assistance program 

• Virtual wellness events 

• Conferences & training budget 

• Regular internal training programs 

• Financial planning with 3% matching Pension  

• Competitive salary 
• Annual bonus structure 

For a career where you can drive our business and shape your future, apply now. 

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We’re looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact.  Our work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.

What you’ll do

About the internship experience

Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products. 

Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission. As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results.

We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry.

Responsibilities

You will:

• Partner closely with Data Scientists, Data Analysts, and business partners to drive business impact through rigorous analytical solutions
• Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success
• Influence business actions and strategy by developing actionable insights through metrics and dashboards.
• Drive the collection of new data and the refinement of existing data sources.
• Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
• Present your work to the Data Science team, partner teams, and fellow interns

Who you are

Minimum requirements

We’re looking for someone who has:

• Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027
• Experience with a scientific computing language (such as Python, R, etc) and SQL. We believe new programming languages can be learned if the fundamentals and general knowledge are present!
• Knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
• Experience communicating and collaborating with multidisciplinary stakeholders in a team environment

Preferred qualifications

You also likely have:

• Experience writing and debugging data pipelines
• Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via experience from previous internships or other multi-person projects
• Ability to learn new systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts

** This role is not eligible for hire in the United States - we are hiring only in Toronto, Ontario, Canada for summer 2026.

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

About this role

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive. 

As a member of the Brand Data Science team working on Listing Quality, you will be responsible for improving the quality of product listings to help retailers find and evaluate products on Faire. You will use ML and AI to tackle critical challenges, such as enhancing image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human-in-the-loop training to create high performance solutions. This space has been evolving rapidly with advancements in AI and you will be at the forefront of applying the latest technology to drive real-world impact. You will independently design and implement solutions and work with the cross-functional Listing Quality pod, including product, design, engineering, analytics, and operations, to solve problems end-to-end.

What you’ll do

• Drive data science vision, strategy, and execution on Listing Quality, using ML and AI solutions to improve the quality of Faire’s product listings.
• Use deep learning, LLM fine tuning, and human-in-the-loop training to automatically detect and address issues with high accuracy.
• Act as a lead on the cross-functional Listing Quality pod, thinking end-to-end about brand and retailer experiences.

Qualifications

• 3+ years of industry experience using machine learning to solve real-world problems
• Experience with relevant business problems (e.g. e-commerce)
• Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human-in-the-loop machine learning)
• Strong programming skills
• An excitement and willingness to learn new tools and techniques
• The ability to design and implement ML solutions without supervision
• Strong communication skills and the ability to work in a highly cross-functional team 

Great to Haves:

• Master’s or PhD in Computer Science, Statistics, or related STEM fields is highly recommended
• Previous experience in listing quality for e-commerce
• Previous experience in supervised fine tuning of multi-modal LLMs
• Experience deploying and optimizing LLM inference systems at scale (10B+ tokens), with focus on cost efficiency and product impact

Salary Range

Canada: the pay range for this role is $180,000 to $247,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

About this role

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive. 

As a member of the Brand Data Science team working on Listing Quality, you will be responsible for improving the quality of product listings to help retailers find and evaluate products on Faire. You will use ML and AI to tackle critical challenges, such as enhancing image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human-in-the-loop training to create high performance solutions. This space has been evolving rapidly with advancements in AI and you will be at the forefront of applying the latest technology to drive real-world impact. You will independently design and implement solutions and work with the cross-functional Listing Quality pod, including product, design, engineering, analytics, and operations, to solve problems end-to-end.

What you’ll do

• Drive data science vision, strategy, and execution on Listing Quality, using ML and AI solutions to improve the quality of Faire’s product listings.
• Use deep learning, LLM fine tuning, and human-in-the-loop training to automatically detect and address issues with high accuracy.
• Act as a lead on the cross-functional Listing Quality pod, thinking end-to-end about brand and retailer experiences.

Qualifications

• 3+ years of industry experience using machine learning to solve real-world problems
• Experience with relevant business problems (e.g. e-commerce)
• Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human-in-the-loop machine learning)
• Strong programming skills
• An excitement and willingness to learn new tools and techniques
• The ability to design and implement ML solutions without supervision
• Strong communication skills and the ability to work in a highly cross-functional team 

Great to Haves:

• Master’s or PhD in Computer Science, Statistics, or related STEM fields is highly recommended
• Previous experience in listing quality for e-commerce
• Previous experience in supervised fine tuning of multi-modal LLMs
• Experience deploying and optimizing LLM inference systems at scale (10B+ tokens), with focus on cost efficiency and product impact

Salary Range

San Francisco: the pay range for this role is $211,000 to $290,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About the Role

We’re looking for an Applied Scientist (ALL LEVELS) to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our valuation systems — ensuring we provide the most accurate and transparent pricing possible — the scope goes well beyond pricing. You’ll work across a range of challenging ML problems, from multi-modal modeling to operational optimization, helping us rethink how we use structured and unstructured data to make better decisions for our customers.

What You'll Need

• Strong software engineering and coding skills in Python, with experience contributing to production codebases
  
  
• Experience developing and deploying ML models end-to-end — from research and prototyping to implementation in production systems
  
  
• Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar
  
  
• Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field
  
  
• Solid foundation in statistics and experimental design
  
  
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
  
  

Nice to Have

• Familiarity with Pyspark and distributed data processing
  
  
• Background in search, recommendation systems, or personalization
  
  
• Experience working with large language models (LLMs) or vision-language models (VLMs)
  
  
• A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data
  
  

What You'll Do

• Design and deploy architectural improvements to our deep neural network (DNN)-based home valuation models
  
  
• Build interpretable ML models that can help us explain pricing decisions to customers
  
  
• Incorporate unstructured data — like images, videos, or text — into our forecasting and valuation pipelines using cutting-edge AI models (LLMs, VLMs, etc.)
  
  
• Collaborate with Engineering and Ops to enhance our human-in-the-loop pricing systems
  
  
• Improve the feature engineering and model training pipelines that power our production systems
  
  
• Rethink our risk and optimization models using real-world data and domain insight
  
  

We’re a small, nimble team — there’s ample opportunity to work across the entire research and modeling stack.

Compensation

The base pay range for this position is $156,800-$310,000 annually, plus RSUs. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.

#LI-RO

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

We are looking for a Senior Staff Scientist – Fault-Tolerant Quantum Algorithms to help lead the technical development of highly differentiated quantum solutions that will bring value to society. As a Senior Staff Scientist – Fault-Tolerant Quantum Algorithms, you’ll guide a cross-functional team whose mandate is central to IonQ’s mission to solve the world’s most complex problems using the world’s best quantum computers.

As a technical leader in the field of fault-tolerant algorithms, you will help discover the next generation of quantum applications that will exceed state-of-the-art classical methods. You will be a core member of technical leadership in quantum algorithms, and you will drive research into new quantum algorithms and develop IP, computational resource models, long-term roadmaps, and end-to-end workflows that have the potential to disrupt the field of computing. You will also work closely with product, engineering, marketing, sales, operations, and external customers/partners to brainstorm new ideas, propose complex, multi-year initiatives and represent IonQ at high-visibility technical conferences (often all in a single day)!

Responsibilities: 

• Influence the quantum applications roadmap towards fault-tolerant quantum algorithms that will make a large scientific and commercial impact by leading the origination, execution, and optimization of novel, end-to-end quantum algorithms. Guide other team members towards this goal.
• Perform detailed resource analyses of quantum algorithms and perform SWOT analysis of FTQC approaches compared to NISQ and/or classical methods.
• Provide trusted expertise and leadership in FTQC algorithms and communicate the current state-of-the-art, scaling behaviors, trade offs, cross-over points, etc. to stakeholders across the company.
• Lead technical interactions across multi-disciplinary teams to identify, define and solve challenging real-world problems using IonQ trapped-ion quantum computers.
• Define, develop, and drive adoption of industry-leading benchmarking and resource estimation methodologies, metrics, and tools.
• Develop portfolio of foundational IP and high-impact-factor peer-reviewed publications; represent IonQ externally with customer/clients and at conferences.

You’d be a good fit with:

• PhD in physics, mathematics, computer science, or similar field, or comparable field or equivalent work experience + 5 years of professional experience in the quantum computing field
• 13+ years of professional experience or an equivalent combination of education and experience
• Demonstrated expertise in FTQC algorithms that can scale to millions of qubits, billions of gates with line-of-sight to end-customer value: active portfolio of invited talks, repos, licenses, publications and/or patents.
• Active participant in the FTQC algorithm community via, e.g., development of tools (libraries, simulators, compiler), metrics (costing, resource estimation, ROI), and/or community (economic development, standards)
• Relentless dedication to optimizing algorithmic performance (accuracy, time-to-solution) through elegant theoretical equations, as well as engineering optimization
• Mastery of key mathematical techniques used in quantum computing and quantum algorithm development, and a demonstrated ability to communicate scientific results clearly.

You’d be a great fit with: 

• 7+ years of professional work experience developing FT quantum algorithms that align with realistic industry problems such as computer-aided engineering, phase transitions, reaction modeling, cybersecurity, differential equations solving, simulation of physical systems, etc. 
• Deep expertise in quantum algorithms for relevant use cases. This could include quantum simulation (e.g., product formulas, qubitization, qDRIFT, etc.), quantum algorithms and primitives (e.g., block-encodings, LCU, QSP, QSVT, Gibbs sampling, quantum linear systems, etc.), and/or end-to-end fault-tolerant quantum algorithms as applied to detailed use cases.
• Demonstrated expertise in Python and Qiskit or similar quantum SDK; working knowledge of C++.
• Experience proposing, winning, and executing on consultative (paid) contracts; government contracting or defense contracting experience a plus
• Experience commercializing end-to-end software utilizing hybrid computing e.g. CPU + GPU + QPU, Edge, Cloud, etc. Knowledge of CI/CD a plus.

Location: This position can work onsite or hybrid from one of our offices (College Park, MD, Bothell, WA, Toronto, Canada, Gothenburg, Sweden) or fully remote in the US
Travel: 10% domestic and international
Job ID:  1254

The approximate base salary range for this position is $192,979 - $252,659. The total compensation package includes base, bonus, and equity.

We’re looking for a Senior Quantum Applications Scientist - Life Sciences who will be part of a cross-functional team at IonQ whose mission is to deliver the world’s best quantum solutions in life sciences on the world’s best quantum computers to solve the world’s most complex and impactful problems. This role is open as part of IonQ’s Quantum Applications team based in either Gothenburg, Sweden or Toronto, Canada. You will work closely with partners within the life sciences innovation ecosystem and beyond to create new hybrid quantum applications with significant commercial impact.

Responsibilities: 

• Develop impactful hybrid quantum applications, algorithms and solutions in the life sciences domain that promise commercial advantages in practice and at scale.
• Collaborate with quantum compiler, cloud and hardware engineering teams to develop highly optimized hybrid workflows for trapped-ion quantum computers.
• Contribute knowledge of classical and quantum domain-specific algorithms and tools to evaluate and communicate pros and cons, current state-of-the-art, scaling behavior, trade offs, cross-over points, etc.
• Be part of a client-facing team that finds, defines, and solves problems of real-world interest using IonQ trapped-ion quantum computers.
• Build reusable software platforms to grow IonQ’s user base. Integrate first of a kind quantum algorithms into larger end-to-end workflows.

You’d be a good fit with: 

• Doctorate degree in the life sciences domain, or equivalent work experience.
• Hands-on expertise with using and developing computational and ML/AI tools in bioinformatics, molecular biology, development of advanced therapeutics, including a track record of peer-reviewed manuscripts and contributions to code bases.
• Demonstrated experience developing, applying, validating quantum computing algorithms and solutions in the life sciences domain, including prototyping solutions using Python and quantum SDKs like Qiskit, PennyLane, Cirq.
• Desire to work closely with customers including aligning with time zones and work schedules. Potential for international travel and/or onsite co-location.

You’d be a great fit with:

• Expertise in key mathematical techniques used in quantum computing - linear algebra, matrix decompositions, probability theory, symmetry, computational complexity.
• Success working directly with clients to define and deliver solutions; excellent collaboration and communication skills.

Location: Onsite and/or hybrid from our office in Gothenburg, Sweden or Toronto, Canada
Travel: 10% domestic and international, with a focus on visiting customers and clients
Job ID: 1360

We’re looking for a Staff Quantum Applications Scientist - Life Sciences who will be part of a cross-functional team at IonQ whose mission is to deliver the world’s best quantum solutions in life sciences on the world’s best quantum computers to solve the world’s most complex and impactful problems. This role is open as part of IonQ’s Quantum Applications team based in either Gothenburg, Sweden or Toronto, Canada. You will work closely with partners within the life sciences innovation ecosystem and beyond to create new hybrid quantum applications with significant commercial impact.

Responsibilities: 

• Originate and lead development of impactful hybrid quantum applications, algorithms and solutions in the life sciences domain that promise commercial advantages in practice and at scale.
• Collaborate with quantum compiler, cloud and hardware engineering teams to develop highly optimized hybrid workflows for trapped-ion quantum computers.
• Contribute knowledge of classical and quantum domain-specific algorithms and tools to evaluate and communicate pros and cons, current state-of-the-art, scaling behavior, trade offs, cross-over points, etc.
• Lead constructive technical interactions with client teams to find, define, and solve problems of real-world interest using IonQ trapped-ion quantum computers.
• Represent the team in client and stakeholder presentations, develop presentation content and appropriately adapt it to the audience.
• Build reusable software platforms to grow IonQ’s user base. Integrate first of a kind quantum algorithms into larger end-to-end workflows.

You’d be a good fit with: 

• Doctorate degree in the life sciences domain, or equivalent work experience.
• At least 3 years of professional experience using and developing computational and ML/AI tools in bioinformatics, molecular biology, development of advanced therapeutics, including a track record of peer-reviewed manuscripts and contributions to code bases.
• At least 3 years of professional experience developing, applying, validating quantum computing algorithms and solutions in the life sciences domain, including prototyping solutions using Python and quantum SDKs like Qiskit, PennyLane, Cirq.
• Desire to work closely with customers including aligning with time zones and work schedules. Potential for international travel and/or onsite co-location.

You’d be a great fit with:

• Expertise in key mathematical techniques used in quantum computing - linear algebra, matrix decompositions, probability theory, symmetry, computational complexity.
• Success working directly with clients to define and deliver solutions; excellent collaboration and communication skills.

Location: Onsite and/or hybrid from our office in Gothenburg, Sweden or Toronto, Canada
Travel: 10% domestic and international, with a focus on visiting customers and clients
Job ID: 1361

We are looking for a Staff Scientist – Fault-Tolerant Quantum Algorithms to lead the technical development in utilizing IonQ’s quantum computers to create highly differentiated quantum solutions that will bring value to society. As a Staff Scientist – Fault-Tolerant Quantum Algorithms, you’ll be a core member of a cross-functional team whose mandate is central to IonQ’s mission to solve the world’s most complex problems using the world’s best quantum computers.

As a hands-on expert in fault-tolerant algorithms, you will help discover the next generation of quantum applications that are poised to deliver results exceeding state-of-the-art classical methods. You will play a key role in developing quantum algorithms, core IP, computational resource models, long-term roadmaps, and end-to-end workflows that have the potential to disrupt the field of computing. You will also work closely with product, engineering, marketing, sales, operations, and external customers/partners to brainstorm new ideas, propose complex, multi-year initiatives and represent IonQ at high-visibility technical conferences (often all in a single day)!

Responsibilities: 

• Lead hands-on development of novel fault-tolerant quantum algorithms that will make a large scientific and commercial impact across a wide range of industry verticals.
• Perform detailed resource analyses of quantum algorithms and perform SWOT analysis of FTQC approaches as compared to NISQ and/or classical methods.
• Provide trusted expertise in FTQC algorithms and communicate the current state-of-the-art, scaling behaviors, trade offs, cross-over points, etc. to stakeholders across the company.
• Drive constructive technical interactions across multi-disciplinary teams to identify, define and solve challenging real-world problems using IonQ trapped-ion quantum computers.
• Develop and drive adoption of industry-leading benchmarking and resource estimation methodologies, metrics, and tools.
• Develop portfolio of foundational IP and high-impact-factor peer-reviewed publications; represent IonQ externally with customer/clients and at conferences.

You’d be a good fit with:

• PhD in physics, mathematics, computer science, or similar field, or comparable field or equivalent work experience + 3 years of professional experience in the quantum computing field
• Demonstrated expertise in FTQC algorithms that can scale to millions of qubits, billions of gates with line-of-sight to end-customer value: active portfolio of invited talks, repos, licenses, publications and/or patents
• Active participant in the FTQC algorithm community via, e.g., development of tools (libraries, simulators, compiler), metrics (costing, resource estimation, ROI), and/or community (economic development, standards)
• Relentless dedication to optimizing algorithmic performance (accuracy, time-to-solution) through elegant theoretical equations, as well as engineering optimization 
• Mastery of key mathematical techniques used in quantum computing and quantum algorithm development, and a demonstrated ability to communicate scientific results clearly.

You’d be a great fit with: 

• 5+ years of professional work experience developing end-to-end solutions for realistic industry problems such as computer-aided engineering, cybersecurity, chemistry, etc.
• Experience working with quantum algorithms for relevant use cases. This could include quantum simulation (e.g., product formulas, qubitization, qDRIFT, etc.), quantum algorithms and primitives (e.g., block-encodings, LCU, QSP, QSVT, Gibbs sampling, quantum linear systems, etc.), and/or end-to-end fault-tolerant quantum algorithms as applied to detailed use cases.
• Demonstrated expertise in Python and Qiskit or similar quantum SDK; working knowledge of C++.
• Experience proposing, winning, and executing on consultative (paid) contracts; government contracting or defense contracting experience a plus
• Experience commercializing end-to-end software utilizing hybrid computing e.g. CPU + GPU + QPU, Edge, Cloud, etc. Knowledge of CI/CD a plus.

Location: This position can work onsite or hybrid from one of our offices (College Park, MD, Bothell, WA, Toronto, Canada, Gothenburg, Sweden) or fully remote in the US
Travel: 10% domestic and international
Job ID:  1058

The approximate base salary range for this position is $167,808 - $219,704. The total compensation package includes base, bonus, and equity.

Why job seekers choose Geotab:

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. 

The Brokerage Data Science team uses data to inform automated modeling decisions and generate insights that guide product and business strategy. The team works closely with product, engineering, and operations partners to improve how customers engage with Robinhood’s platform. You’ll contribute to shaping personalized product experiences that support customers throughout their investing journey!

As a Senior Data Scientist, ML, you will lead the development of recommendation systems for prediction markets, one of Robinhood’s fastest-growing areas. You will work closely with product managers and engineers to identify opportunities for personalization, design modeling approaches, and implement solutions that improve customer engagement. This role starts with building personalization for prediction markets and will expand to additional product surfaces as the strategy evolves.

This role is based in our Menlo Park, CA and New York, NY office(s), with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

What you’ll do

• Build and improve recommendation system algorithms to personalize customer experiences across prediction markets and other product surfaces
• Partner with product managers to identify areas for personalization and define measurable success criteria
• Develop features and models that improve relevance and user interaction with our prediction markets offerings
• Collaborate with software and machine learning engineers to design and implement scalable feature pipelines and the ranking systems
• Design and run experiments to evaluate model performance and measure incremental impact on customer engagement

What you bring

• You have 5+ years of experience building recommendation systems in customer-facing products (e.g., streaming, marketplace, or on-demand platforms)
• You are proficient in Python and SQL and have strong experience with machine learning systems and production modeling
• You have experience with experimentation methods and causal inference to evaluate model performance
• You communicate clearly and collaborate effectively with product, engineering, and data science partners
• You demonstrate ownership by driving projects from concept through implementation

What we offer

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

We are TRADER, a Canadian leader in digital automotive solutions. Our flagship brands - AutoTrader.ca, AutoSync, Dealertrack Canada and CMS - help Canadians buy, sell, and finance vehicles with confidence. 

Learn more at tradercorporation.com. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond. 

As Senior Data Scientist, you will be key contributor within our global Data Science organization, shaping AI and machine learning systems that sit at the core of our marketplace platforms across Europe and Canada. 

You design, build, and operate machine learning and GenAI systems that run in production and matter to the business. You work on complex, ambiguous problems, exercise strong technical judgment, and take responsibility for outcomes - not just models. While this is a hands-on role, you are also expected to influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed. This position is permanent and based in Toronto. 

What you’ll do 

• Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement 

• Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability 

• Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes 

• Operate and evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints 

• Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems 

What you’ll need  

• Advanced degree in Computer Science, Engineering, Mathematics, or a comparable field 

• 5+ years of experience building and owning production ML systems end-to-end in a real-world environment 

• Strong hands-on expertise in Python and modern ML frameworks, with the ability to ship, operate, and evolve ML systems in production 

• Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale 

• Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations 

• Ability to influence technical decisions through clear judgment and collaboration, not formal authority 

• Experience supporting and guiding more junior data scientists through hands-on collaboration, code reviews, and technical feedback 

• Strong sense of ownership and accountability for outcomes, with a pragmatic approach to trade-offs and delivery 

What’s in it for you 

We understand that there is life at work and life outside of work. Here are a few benefits that support us to be our creative best.   

• Gym discounts 
• Employee and Family Assistance program 
• Virtual wellness events 
• Conferences & training budget 
• Regular internal training programs 
• Financial planning with 3% matching Pension  
• Competitive salary 
• Annual bonus structure 

The base salary range for this position is CAD $180k – $120k.

This range reflects the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role, the total rewards package may also include benefits, bonus, and other employee offerings. 

Use of Artificial Intelligence in Hiring: We use artificial intelligence (“AI”) in our hiring process, including to screen, assess, or select applicants for this position.

Vacancy Status: This job posting is for an existing vacancy. 

WHAT YOU'LL DO

Our Data Scientist, AI Deployment team is a group of creative technical experts who design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. In this role, you will:

• Design ML use cases from the ground up — scoping solutions that optimize for real business value, accounting for the complexity of modern marketing journeys, and proactively identifying risks to set each engagement up for success
• Build and own the full ML pipeline —  taking customers' raw data through transformation, model training, and activation, so that model decisions are delivered to personalize experiences for millions of end users
• Drive customer success by providing ongoing technical guidance that ensures data science performance, successful adoption, and measurable outcomes
• Extend product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements
• Partner with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward
• Shape BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in Ontario, the pay range at the start of employment for this position is expected to be between CA$112,000 - CA$168,000/year, with an expected On Target Earnings (OTE) between CA$125,000 - CA$188,000/year (including performance-based or variable compensation (bonus or commission). Your particular offer may vary depending on multiple individual factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

MaintainX is the world’s leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We’re a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities.

We help 12,000+ organizations—including Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell—achieve operational excellence and reliability at scale.

Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion.

As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure.

What you’ll do:

• Design, develop and optimize machine learning models for fault detection and classification end-to-end e.g. data and training modeling choices to evaluation strategies and production constraints.
• Perform EDA on vibration, OT and time-series data to uncover insights and identify patterns indicative of faults or anomalies.
• Conduct experiments and evaluation of various algorithms on time-series modeling, signal processing, and statistical methods, to optimize model performance.
• Partner with PMs in product feature discovery and roadmap prioritization through validating product hypotheses, designing success metrics and quantifying end user impact
• Collaborate with domain experts to validate findings and ensure alignment with real-world applications.
• Engage with your community of peers to challenge the status quo, improve our shared ways of working, and influence overall architecture decisions, continuing to foster our culture of Applied Science excellence
• On-call duties

About you:

• Master’s or Ph.D. in Computer Science, Data Science, Mechanical Engineering, Electrical Engineering, or a related field with a focus on condition monitoring or machine learning applications.
• 5+ years of proven programming skills using standard ML tools such as Python, PyTorch, Tensorflow etc.
• Strong foundational knowledge in machine learning, data science, and statistics
• Familiarity with time-series modeling techniques and feature engineering.
• Ability to deliver production-grade code that is well-tested, maintainable, and evaluated through rigorous experimentation.

Bonus skills: 

• Hands-on experience developing models for OT and vibration analysis, condition monitoring, and fault detection or classification.
• Familiarity with signal processing techniques (e.g., Fourier transforms, wavelet analysis) and their application to OT and vibration data.

What’s in it for you:

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take what you need PTO.
• A high impact Culture:
• You’ll work with Smart, Humble Optimists across the globe.
• Meritocratic environment where ideas and outcomes are publicly celebrated.

About us:

We exist to make the lives of frontline and maintenance teams easier by building software that meets their real-world needs. Our product transforms how 80% of the global workforce—those who don’t sit behind a desk—manage their operations, assets, and teams.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

About the Role

We are seeking an exceptional Senior Data Scientist to join our centralized Data organization. In this role, you will be embedded within our consumer and seller experience groups, working closely with cross-functional partners across product, engineering, design, and leadership. You will leverage data to generate deep insights that drive product strategy and create a world-class experience for our users. You'll work with terabytes of data to understand user behavior and directly impact customer satisfaction and business growth.

What You'll Do

• Develop and implement advanced analytics to drive product strategy and enhance the consumer and seller experience.
  
  
• Conduct deep-dive statistical analyses on large datasets to uncover user behavior insights and identify key business opportunities.
  
  
• Partner with product, engineering, and operations teams to identify opportunities to improve the user journey through data-driven insights.
  
  
• Design and execute A/B tests and other experiment types, like multi-armed bandit tests, to measure the impact of product changes and optimize the user experience.
  
  
• Build scalable data pipelines and reporting dashboards to deliver insights to stakeholders.
  
  
• Present findings and strategic recommendations to executive leadership.
  
  
• Contribute to the team and company knowledge base.
  
  

What You'll Need

• Advanced proficiency in SQL for complex data manipulation and analysis.
  
  
• Strong skills in Python for data analysis and visualization.
  
  
• Deep understanding of statistics, A/B testing, and experimental design.
  
  
• Excellent communication skills with the ability to present to executive leadership.
  
  
• Strong business intuition and the ability to translate technical findings into business recommendations.
  
  
• A self-motivated individual with a desire to solve complex, open-ended problems.
  
   
  
  

Education & Experience

Bachelor's degree or higher in a quantitative field such as Statistics, Economics, Mathematics, or Computer Science.

8+ years of experience in data science, product analytics, or a similar quantitative role.

3+ years of experience in e-commerce, two-sided marketplaces, or consumer-facing products preferred.

What We Offer

• Executive-level visibility with a direct impact on core business metrics.
  
  
• Opportunity to work on high-impact analytics projects that shape product strategy.
  
  
• Hybrid work model: 4 days in office, 1 day remote flexibility.
  
  
• Collaborative culture with cross-functional team integration.
  
  
• A fast-paced, high-growth environment with significant learning opportunities
  
  

Compensation

Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.  All compensation parameters are based on experience.

LI-RO

Data Scientist, Pricing

Location: Hyrbrid 4 onsite, 1 remote Seattle WA. 

Opendoor is transforming one of the largest, most complex markets in the world — residential real estate — using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company’s financial performance.

We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You’ll operate at the intersection of economics, machine learning, experimentation, and product strategy — tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory — and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.

What You’ll Do

• Build and maintain pricing metrics, dashboards, and frameworks.
• Run experiments and causal analyses to measure impact and drive decisions.
• Develop predictive + statistical models that improve pricing accuracy.
• Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
• Deliver insights and narratives that inform executive strategy.

Skills & Qualifications

• Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
• Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
• Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
• Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
• High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
• Effective communicator — able to tell the story behind the model to both highly technical and non-technical audiences.
• 8+ years of experience in data science, product analytics, or a similar quantitative role.

Base salary range for this role varies. Generally, the base salary range is $186,000 – $256,000 annually + RSUs + ESPP + additional employee benefits (medical/dental/vision, life insurance, unlimited PTO, 401K).

#LI-RO

#

#LI-KC1

Data Scientist, Pricing

Location: In office 4 days a week; Ontario, Canada.

Opendoor is transforming one of the largest, most complex markets in the world — residential real estate — using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company’s financial performance.

We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You’ll operate at the intersection of economics, machine learning, experimentation, and product strategy — tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory — and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.

What You’ll Do

• Build and maintain pricing metrics, dashboards, and frameworks.
• Run experiments and causal analyses to measure impact and drive decisions.
• Develop predictive + statistical models that improve pricing accuracy.
• Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
• Deliver insights and narratives that inform executive strategy.

Skills & Qualifications

• Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
• Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
• Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
• Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
• High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
• Effective communicator — able to tell the story behind the model to both highly technical and non-technical audiences.
• 8+ years of experience in data science, product analytics, or a similar quantitative role.

Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.  All compensation parameters are based on experience.

#LI-RO

#LI-KC1

The role

Are you passionate about food? Do you consider yourself an expert and enthusiast in developing and deploying large-scale recommender systems? Then this position might be the perfect fit for you!

You will join a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, you will play a pivotal role in designing, implementing, and improving our personalized recommendation algorithms for culinary products across HelloFresh’s global markets. In this role, you can expect to have a large and tangible impact on customer experience and business growth by ensuring customers always see the most relevant and appealing menu options. You will work closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, together delivering statistical solutions and ML models to production.

To succeed in this role you should be curious, able to deal with uncertainty, a fast learner, and someone who relentlessly prioritizes problem statements and tailors the solution accordingly. You should also be comfortable suggesting multiple solutions based on your experience, and prioritizing tasks based on effort and potential impact. As a senior member of the team, you will be expected to work independently when necessary, as well as support other team members occasionally. 

What you’ll do

• Join and become an integral part of a high-impact team covering menu personalization.
• Contribute to designing and implementing the next generation of our recommender models, from experimentation and data collection to operationalization and closely aligning them with non-technical stakeholders.
• Shape and transform the future of customer experience at HelloFresh by proposing new personalization approaches and evolving the statistical and ML models in pace with future company strategies.
• Design and execute A/B tests to measure the impact of new recommendation strategies on key metrics.
• Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, Claude (AI), as well as our in-house MLOPs tools.
• Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete, data-driven personalization strategies.
• Analyze the performance of our models to understand customer behavior, and come up with improvements.
• Contribute to a collaborative and knowledge-sharing environment.

What you’ll bring

• Proven track record of scientific work in your Bachelor's, Master's, or PhD in computer science, statistics, physics, economics, mathematics, data science or similar.
• Long-term (3+ yrs) work experience as a (senior) data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.
• In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of building and maintaining a modern recommender system.
• Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib. (Experience in Databricks and PySpark is a plus).
• Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.
• Experience with software development practices and tools (Git, CI/CD, Docker, AWS).
• You love to learn, are a critical thinker and creative problem solver who strives for excellence.
• You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment.
• Exceptional communication and collaboration capabilities.
• Experience working with and leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, code generation, and documentation.

Interacting with product managers, UX designers, data and backend engineers, as well as business stakeholders, is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their statistical modeling and machine learning skills to a wide range of business problems in the personalization space while also acting as an ambassador to coach team members and stakeholders.

Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills, and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

#DATA

About The Team 

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems. 

About The Role 

Most AI research today is shaped by the constraints of existing hardware. This role starts from the other direction: what would you build if the architecture let you rethink the fundamentals? You will design and develop AI models and training methodologies on wafer-scale hardware, working at the level of optimization theory, model architecture, and statistical foundations rather than assembling existing components. 

The ATG sits at the intersection of AI, computational science, and computer architecture, and your work will draw on all three. You will collaborate closely with Cerebras’ ASIC, compiler, kernel, and AI teams as well as external partners at universities and national laboratories. 

What You Will Do 

• Design AI models and training methods from first principles, leveraging architectural properties of wafer-scale hardware that are unavailable on conventional platforms. 
• Investigate how techniques from computational science—numerical methods, PDE solvers, simulation—can inform and advance AI model design, and explore hybrid workflows that couple simulation and learning. 
• Develop a deep understanding of the hardware substrate and use it to guide algorithmic choices: model structure, optimization strategy, memory access patterns, numerical precision. 
• Publish findings and present at top-tier venues (NeurIPS, ICML, ICLR, etc.); represent Cerebras in the broader AI/ML research community. 
• Inform the design of future Cerebras hardware and software by identifying the computational patterns that matter most for next-generation AI workloads. 

What We Are Looking For 

• PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field preferred; exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply. 
• Mathematical maturity: comfort with the theory behind gradient methods, loss landscapes, generalization, and the relationship between model structure and data statistics. 
• Track record of published research at top-tier AI or computational science venues. 
• Proficiency in Python and PyTorch; comfort with C or other low-level languages is a strong signal. 
• Excellent communication and interpersonal skills: able to present complex technical material to both ML and systems audiences, and to collaborate effectively in a fast-paced, small-team environment. 

Why This Opportunity Is Exciting And Unique 

• You will have direct access to hardware that changes what’s algorithmically possible. Tens of PB/s of memory bandwidth and fine-grained dataflow execution open design spaces that don’t exist on GPU clusters. 
• You will work alongside researchers in computational science, computer architecture, and performance engineering. The synthesis across these fields is central to ATG’s approach. 
• Your research will influence silicon - ATG’s findings directly shape the design of future Cerebras chips and systems. 

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply. 

About The Role

As an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the world. 

You will work closely with researchers and senior engineers to implement and improve workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. This includes building training pipelines, debugging complex system behaviors, improving model quality, and iterating on data and evaluation strategies. Your contributions will help translate cutting-edge ML ideas into reliable, production-ready systems that solve real-world problems. 

This role is ideal for candidates who enjoy hands-on engineering, want to build deep intuition for ML systems, and are excited about working on LLMs and reinforcement learning in practice, not just in theory. 

Responsibilities 

• Apply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance.
• Build and maintain evaluation pipelines to measure model performance across tasks and domains.
• Debug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation.
• Collaborate with researchers to translate ML ideas into efficient, scalable implementation.
• Design, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment).
• Work with large datasets, including dataset generation, filtering, and synthetic data approaches.
• Optimize training and inference workflows for performance, efficiency, and reliability.
• Contribute high-quality, maintainable code to shared ML infrastructure. 

Skills & Qualifications    

•  Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 0 - 5 years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels. 
• Strong programming skills in Python.
• Experience with ML frameworks such as PyTorch.
• Solid understanding of machine learning fundamentals.
• Familiarity with deep learning architectures, particularly transformers.
• Ability to read and understand modern ML papers and implement key ideas.

Preferred Skills & Qualifications 

• Experience working with large language models (training, fine-tuning, and evaluation).
• Familiarity with reinforcement learning concepts.
• Experience with distributed training frameworks (e.g., FSDP, Megatron).
• Experience working with large-scale datasets and data pipelines.
• Experience debugging or optimizing ML systems for performance.
  • Contributions to meaningful codebases, projects, or open-source systems 

Are you driven by data, inspired by innovation, and eager to shape the future of insurance?

Join a fast-growing Canadian P&C insurer where you'll play a pivotal role in advancing our Actuarial Services function. We're building on a solid foundation—powered by cutting-edge technology, a robust enterprise data analytics team, and bold investments in AI. With this groundwork in place our talented team is now focused on scaling and refining our capabilities.

We're looking for bright, analytical minds to help bring our strategy to life. If you're passionate about solving complex problems and want to explore Pricing, Underwriting, and Claims, we want to hear from you.

Senior Data Scientist

We're looking for a Senior Data Scientist to join our growing team and build the next generation of predictive analytics solutions. In this role, you won’t just be crunching numbers, you’ll be using machine learning (ML) and artificial intelligence (AI) models to transform raw data into powerful insights that drive our business forward.

This is an opportunity to directly contribute to our core operations, working alongside a supportive team who are invested in your growth. If you have a passion for data and a desire to see your work make a tangible impact, this role is for you.

What you'll do:

• Deliver value through data-driven algorithms and models: You will apply the right mix of ML and AI to solve high-impact business problems. You’ll partner with stakeholders to select and defend the best model architecture and explainability approaches to balance performance, interpretability, and trade-offs.
• Embed ML/AI into core business capabilities: You will build deep expertise in P&C insurance workflows and translate that knowledge into practical ML/AI-powered analyses, decision tools, and visualizations that improve how work gets done.
• Partner with stakeholders to ensure adoption, value, and model integrity: You’ll align with stakeholders on goals and success metrics, then pressure-test solutions against real constraints to ensure they’re feasible and valuable. You will communicate your insights and recommendations with clarity and confidence to both technical and non-technical audiences.
• Invest in Your Future: We're committed to your professional development. You'll engage in project-specific research to continually grow your skills and have the unique opportunity to collaborate with our Claims and Finance departments.

 What You’ll Need to Succeed

• Education: You have a master’s degree in a quantitative or technical discipline
• Experience: You have 3–5 years of experience in an ML/AI development role, with experience deploying ML / AI models into production and associated governance procedures.
• Technical Skills: You have a broad understanding of modern ML architectures, familiarity with cloud and ML platforms. You have strong Python programming skills and experience with various ML libraries.
• Core Competencies: You have excellent analytical, quantitative, and critical thinking skills. You are highly analytical and use your communication and collaboration skills to engage with stakeholders to solve problems.

If you're ready to be a core part of our mission and make a tangible impact from day one, we want to hear from you.

#LI-Hybrid

The expected base salary range for this position is $79,500 - $129,500. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. You have the potential to earn more through Gore Mutual’s discretionary bonus program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.

Please note: This range reflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels. During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.

Gore Mutual is proud to offer a comprehensive total rewards package which includes extended health and dental benefits, disability insurance, retirement plan matching, paid time off, recognition and perk programs.

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll help drive the ML algorithm strategy and system design behind one of the most critical levers for customer value and company growth—Search Ads. You’ll lead the advancement of real-time systems that decide which ads to show for a query, where to place them, and how to optimize for relevance, marketplace health, and advertiser outcomes. This role mirrors many of the technical expectations of Faire’s organic Search roles (modern NLP/LLMs, query understanding, real-time ranking), while operating in an ads environment with auctions, budgets, and pacing constraints.

You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, and structured behavioral data to deliver highly relevant sponsored results for any given query.

What You'll Do

• Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals.
• Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features.
• Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments.
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire should be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 4+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval.
• Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization.
• Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact.
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll help drive the ML algorithm strategy and system design behind one of the most critical levers for customer value and company growth—Search Ads. You’ll lead the advancement of real-time systems that decide which ads to show for a query, where to place them, and how to optimize for relevance, marketplace health, and advertiser outcomes. This role mirrors many of the technical expectations of Faire’s organic Search roles (modern NLP/LLMs, query understanding, real-time ranking), while operating in an ads environment with auctions, budgets, and pacing constraints.

You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, and structured behavioral data to deliver highly relevant sponsored results for any given query.

What You'll Do

• Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals.
• Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features.
• Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments.
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire should be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 2+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval.
• Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization.
• Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact.
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $165,500 to $227,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll shape the future of our ads marketplace and auction system at Faire—spanning auction design, bidding strategy, pacing, pricing, and budget optimization. Our in-house stack gives us unique end-to-end ownership, and our first-party conversion data allows us to train highly effective models and optimize for real, business-critical outcomes on behalf of our brands.

This is a rare opportunity to be an early contributor to a fast-growing team in an incredibly strategic area of the business. Ads is a major company priority and you'll have a massive impact in shaping the platform that connects independent retailers and brands. You’ll work closely with engineers, product managers, and designers to launch and iterate on systems that are not just technically sophisticated, but also directly drive improvements to the bottom line for both brands and Faire.

What You'll Do

• Own the end-to-end development of ML models across the ads bidding stack—from problem framing, solution design, modeling, and implementation to deployment, experimentation, and impact measurement.
• Build best-in-class models and algorithms for auction optimization, bid shading and bid multipliers, budget allocation, pacing, and advertiser ROI/ROAS optimization—drawing from marketplace optimization and experimentation best practices.
• Define and improve bidding and pacing strategies that balance advertiser performance, marketplace health, and platform economics (e.g., spend smoothing, delivery guarantees, seasonal demand, and inventory constraints).
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire *should* be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 4+ years of industry experience using machine learning to solve real-world problems, ideally in Ads, Marketplace Optimization, Pricing, Auctions, or a related large-scale production domain.
• Demonstrated ownership of the full ML lifecycle: from scoping and design through training, deployment, A/B testing, and iteration.
• Strong programming skills.
• Experience with relational databases and SQL.
• The ability to contribute to team strategy and to lead model development without supervision.
• Strong communication skills and the ability to work with others in a closely collaborative team environment.

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll shape the future of our ads marketplace and auction system at Faire—spanning auction design, bidding strategy, pacing, pricing, and budget optimization. Our in-house stack gives us unique end-to-end ownership, and our first-party conversion data allows us to train highly effective models and optimize for real, business-critical outcomes on behalf of our brands.

This is a rare opportunity to be an early contributor to a fast-growing team in an incredibly strategic area of the business. Ads is a major company priority and you'll have a massive impact in shaping the platform that connects independent retailers and brands. You’ll work closely with engineers, product managers, and designers to launch and iterate on systems that are not just technically sophisticated, but also directly drive improvements to the bottom line for both brands and Faire.

What You'll Do

• Own the end-to-end development of ML models across the ads bidding stack—from problem framing, solution design, modeling, and implementation to deployment, experimentation, and impact measurement.
• Build best-in-class models and algorithms for auction optimization, bid shading and bid multipliers, budget allocation, pacing, and advertiser ROI/ROAS optimization—drawing from marketplace optimization and experimentation best practices.
• Define and improve bidding and pacing strategies that balance advertiser performance, marketplace health, and platform economics (e.g., spend smoothing, delivery guarantees, seasonal demand, and inventory constraints).
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire *should* be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 2+ years of industry experience using machine learning to solve real-world problems, ideally in Ads, Marketplace Optimization, Pricing, Auctions, or a related large-scale production domain.
• Demonstrated ownership of the full ML lifecycle: from scoping and design through training, deployment, A/B testing, and iteration.
• Strong programming skills.
• Experience with relational databases and SQL.
• The ability to contribute to team strategy and to lead model development without supervision.
• Strong communication skills and the ability to work with others in a closely collaborative team environment.

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $165,500 to $227,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Lightmatter builds chips that enable extreme-scale artificial intelligence computing clusters. If you're a collaborative engineer or scientist who has a passion for innovation, solving challenging technical problems, and doing impactful work like building the world's first optical computers, consider joining the team at Lightmatter!

We are hiring a Sr. Mixed-Signal Digital Architect. The selected candidate will partner with external facing teams at Lightmatter and the internal engineering team to deliver groundbreaking products to the market. As an architect, you will provide detailed technical documents that describe what needs to be built to the engineering team. This will require a solid understanding of process technology, state of the art in chip design, and clear communication skills. In this role, you will be defining the architecture of the digital circuits that enable a ground-breaking photonic-based communication fabric. Your work will not only enable the AMS/photonic devices at low-level but also enable the necessary interfaces with the firmware/software. You will interact directly with our vendors and our customers. You will also define the product and technological roadmaps along with suitable design and verification methodologies.

You will report directly to the Chief Scientist, but you will also work closely with our digital, analog, photonic, and software teams. We are particularly looking for someone with expertise in architecting digital circuits to enable high-speed AMS circuits, with a strong preference for someone with experience in photonic circuits.

Join a tight-knit team where each individual’s contributions directly influence the success of the company and product. You'll have the opportunity to build a new kind of computer from the ground up and to solve groundbreaking challenges along the way. Work with people who love to build and who thrive in technically diverse environments where great ideas are prioritized.

Responsibilities

• Be the digital architecture owner of Lightmatter’s Passage product. Work closely with the rest of the architecture team, chip-design team, and the software team.
• Responsible for the digital architecture from initial concept through high-volume production. Work closely with the technical program manager(s) to plan, organize, and execute.
• Architect and specify system level digital designs integrating complex AMS and photonic circuits. These circuits include stabilization circuits of AMS & photonic devices; line-rate DSP, FEC, CRC; and tuning & adaptation of analog front-end components.   
• Work closely with test and validation engineers to validate hardware against simulation prediction.
• Actively collaborate with the RTL and DV teams to enable block-level implementation and verification, respectively.
• Actively enable the firmware team to develop the recipe for hardware bringup and validation.
• Author, review, and validate architectural specifications. With the product and applications engineering teams, they also produce customer-facing product datasheets and reference designs.
• Identify possible improvements as well as possible pitfalls (including mitigation strategies) around executing the proposed architectures. 

Qualifications 

• 12+ years and a Masters’ degree in Electrical or Computer Engineering
• In-depth knowledge of power-efficient digital design flow for high-speed AMS electronics, preferably on photonic communication channels.
• In-depth knowledge of digital circuit design in a high-speed analog/photonic link, including device bring-up, control, and digital signal processing.
• Demonstrated strong problem solving skills specifically pertaining to problems that do not have obvious solutions.
• Demonstrated strong customer communication, with timely responses and consistently positive feedback

Preferred Qualifications

• Understanding of SerDes PCS layer and equalization along with forward error-correction schemes.
• Ability and desire to collaborate in a cross-disciplinary team: from hardware to software.

Lightmatter builds chips that enable extreme-scale artificial intelligence computing clusters. If you're a collaborative engineer or scientist who has a passion for innovation, solving challenging technical problems, and doing impactful work like building the world's first optical computers, consider joining the team at Lightmatter!

We are hiring a Sr. Mixed-Signal Digital Architect. The selected candidate will partner with external facing teams at Lightmatter and the internal engineering team to deliver groundbreaking products to the market. As an architect, you will provide detailed technical documents that describe what needs to be built to the engineering team. This will require a solid understanding of process technology, state of the art in chip design, and clear communication skills. In this role, you will be defining the architecture of the digital circuits that enable a ground-breaking photonic-based communication fabric. Your work will not only enable the AMS/photonic devices at low-level but also enable the necessary interfaces with the firmware/software. You will interact directly with our vendors and our customers. You will also define the product and technological roadmaps along with suitable design and verification methodologies.

You will report directly to the Chief Scientist, but you will also work closely with our digital, analog, photonic, and software teams. We are particularly looking for someone with expertise in architecting digital circuits to enable high-speed AMS circuits, with a strong preference for someone with experience in photonic circuits.

Join a tight-knit team where each individual’s contributions directly influence the success of the company and product. You'll have the opportunity to build a new kind of computer from the ground up and to solve groundbreaking challenges along the way. Work with people who love to build and who thrive in technically diverse environments where great ideas are prioritized.

Responsibilities

• Be the digital architecture owner of Lightmatter’s Passage product. Work closely with the rest of the architecture team, chip-design team, and the software team.
• Responsible for the digital architecture from initial concept through high-volume production. Work closely with the technical program manager(s) to plan, organize, and execute.
• Architect and specify system level digital designs integrating complex AMS and photonic circuits. These circuits include stabilization circuits of AMS & photonic devices; line-rate DSP, FEC, CRC; and tuning & adaptation of analog front-end components.   
• Work closely with test and validation engineers to validate hardware against simulation prediction.
• Author, review, and validate architectural specifications. With the product and applications engineering teams, they also produce customer-facing product datasheets and reference designs.
• Identify possible improvements as well as possible pitfalls (including mitigation strategies) around executing the proposed architectures. 

Qualifications 

• 12+ years and a Masters’ degree in Electrical or Computer Engineering
• In-depth knowledge of power-efficient digital design flow for high-speed AMS electronics, preferably on photonic communication channels.
• In-depth knowledge of digital circuit design in a high-speed analog/photonic link, including device bring-up, control, and digital signal processing.
• Demonstrated strong problem solving skills specifically pertaining to problems that do not have obvious solutions.
• Demonstrated strong communication and collaboration internally and externally, with timely responses and consistently positive feedback.

Preferred Qualifications

• Understanding of SerDes PCS layer and equalization along with forward error-correction schemes.
• Ability and desire to collaborate in a cross-disciplinary team: from hardware to software.

About this role

As a Senior Applied AI/ML Scientist on the Search ranking team, you will help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (the primary tool used by customers on any e-commerce site). You will advance real-time search and recommendation systems that power next-generation shopping experiences.

You’ll work at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query.

This is a rare chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, while collaborating closely with a talented team of scientists and engineers.

What you'll do

• Build our next-generation Search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey at Faire
• Leverage LLM to extract multimodal signals (text, visual) to better profile users and their intents. 
• Partner closely with teams across Faire to experiment and improve the ML models for search ranking and beyond.
• Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.
• Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.

You're a great fit if you have...

• 5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking
• A Master’s or PhD in Computer Science, Statistics, or a related STEM field.
• Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark).
• Deep understanding of machine learning best practices (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains.
• A product-focused mindset and a bias toward execution—moving quickly from research papers to prototypes and production.
• Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team.

Bonus points for...

• Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
• Industry experience developing and productizing LLM-based applications and systems in the search domain.
• Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces.
• Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity.
• Familiarity with Kotlin

Salary Range

California: the pay range for this role is $192,000 to $264,000 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Who We Are

At Momentum Financial Services Group, we help people move forward by reimagining how money works for those who need it most. With more than 40 years of experience, we’re the team behind Money Mart—Canada’s largest non-bank branch network—and a leader in financial solutions for underserved communities.

From short-term loans to money transfers and prepaid cards, we power the products, technology, and operations that connect over a million customers a year to the money they need, when they need it.

At MFSG, we come together across teams and departments to create something bigger than ourselves: solutions that remove barriers and give people access to money they might not get anywhere else. Whether you're solving problems, building systems, or shaping strategy, your work fuels real support for real people.

We’ve Got You Covered

Compensation Philosophy: Our strategy is simple—we aim to match the market. We regularly review industry standards to ensure our total rewards package is competitive and fair. This commitment helps us attract and retain talented individuals who share our purpose.

Discretionary Annual Bonus: Enjoy the opportunity for a discretionary bonus based on individual performance and company success.

Comprehensive Benefits: Our benefits include health and dental plans with 100% of the premiums covered. We also offer an Employee Assistance Program to support your mental well-being and provide resources for personal challenges.

Retirement Plans: Plan for your future with our robust retirement savings options, ensuring you’re set for the long haul.

Hybrid Work Environment: Experience the best of both worlds with our hybrid work model, allowing you to balance remote work with in-office. When you're at our corporate head office, enjoy a relaxed and collaborative environment featuring breakout rooms for brainstorming and unwinding, plus a variety of snacks to keep you energized throughout the day.

Perks and Rewards: Enjoy reimbursement for tuition assistance and professional development, discounts through Perkopolis and participate in our rewards and recognition programs to celebrate your contributions.

The Job: Data Scientist

We’re seeking a Data Scientist to develop advanced analytical and machine learning solutions that support credit risk, fraud detection, marketing optimization, and customer segmentation. This role will leverage large-scale data to generate insights, improve decision-making, and drive measurable business impact across the organization.

What You’ll Do

Advanced Analytics & Modeling:

• Design, develop, validate, and deploy predictive and prescriptive models across financial products

• Apply machine learning, statistical, and optimization techniques to solve business challenges such as credit risk, fraud detection, pricing, and customer acquisition

• Ensure models are scalable, compliant, and deliver measurable impact

Data Exploration & Feature Engineering:

• Analyze large and complex datasets to identify patterns and extract meaningful features

• Improve model performance through data-driven insights

Collaboration & Communication:

• Partner with data engineers, product teams, risk teams, and business stakeholders

• Translate business needs into data science solutions and communicate insights effectively

Model Governance & Compliance:

• Ensure models align with regulatory requirements and internal governance standards

• Support audit and validation processes

Continuous Improvement & Innovation:

• Monitor model performance and implement enhancements or retraining

• Explore new tools, techniques, and approaches to improve outcomes

Cross-Functional Initiatives:

• Lead and support projects such as portfolio optimization and customer behavior analysis

• Collaborate across business lines including marketing, operations, and card services

What You’ll Bring to the Table

• 2+ years of experience in financial services, credit risk, fraud analytics, or marketing analytics

• 2+ years of experience applying data science to solve business problems

• Strong experience with SQL, Python, R, or similar analytical tools

• Ability to perform descriptive, diagnostic, predictive, and prescriptive analytics

• Strong problem-solving skills with the ability to translate data into actionable insights

Education + Experience

• Bachelor’s degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, Economics, Finance, or Engineering

• Master’s or PhD in a related field is an asset

Skills & Competencies

• Proficiency in programming languages such as Python (preferred), R, or SAS

• Strong SQL skills for data extraction and analysis

• Experience with machine learning libraries and statistical modeling

• Familiarity with NLP and modern AI techniques (e.g., LLMs) is an asset

• Strong analytical thinking and ability to work with large datasets

Closing

Ready to turn data into impactful insights and drive smarter decisions? Join us and help shape the future of data science at MFSG.

Committed to Equal Opportunity:

MFSG is committed to accommodating applicants up to the point of undue hardship during the recruitment, assessment and selection process. If you are selected for an interview, please notify MFSG if you require accommodation in respect of the materials or procedures used at any time during this process. If you require accommodation, MFSG will work with you to determine how to meet your needs.

Please note: The salary range, inclusive of bonus, for this position is between C$ 95,000 to C$ 105,000.

#SJ