Position Overview:

Come join the team at Zynga making an impact across all of the company’s games - Mobile Game Tech! Do you love developing data models and visualizations to help teams make strategic decisions? This analyst role is a key figure in our cost transparency efforts on the FinOps team, delivering critical insights into service costs. This position also provides dashboards, data visualizations, and analyses for areas that make our org effective at serving our internal customers, allowing all teams to make better decisions.

What You'll Do:

• Lead financial analysis activities with regards to internal cost allocations for technology spend
• Lead data model design and data analysis aspects of the FinOps team’s software development, including close collaboration with other FinOps software engineers
• Engage with customers and stakeholders to design and iterate upon user-facing data visualizations
• Develop data ingestion and normalization to serve data visualizations and dashboards, as well as owning maintenance and ensuring ongoing data quality
• Support FinOps guidelines and work with other teams and partners to implement cost analysis and optimizations for technology spend across Zynga
• Interact with members of Finance and the C-suite with regards to technology cost allocations, forecasts, and ad hoc FinOps-related requests

What You Bring:

• B.S. in Computer Science, Math, Statistics, Engineering, or other quantitative field (or equivalent experience)
• Demonstrated proficiency with Python for data cleaning and data wrangling (pandas, NumPy), and ability to work with source code via pull requests, CICD pipelines, etc
• 8+ years of hands-on experience with the following: SQL, data warehouses, Tableau or similar data visualization tools
• Ability to design monitoring rules for validating data quality within data pipelines
• Experience collaborating with customers to assess their analysis and visualization needs and design solutions that present the data effectively and clearly
• Ability to think through the UI/UX of data visualizations to best serve the target audience's needs
• Comfort interacting with stakeholders at a much more senior level, ability to adjust communication style to the audience
• Experience working autonomously and capable of tackling solo projects with ease

Bonus Points:

• Familiarity with FinOps practices
• Familiarity with financial concepts related to budgeting, forecasts, amortization, etc
• Previous experience with software engineering platforms such as AWS, Splunk, Datadog

What We Offer You:

Zynga offers a world-class benefits package that helps support and balance the needs of our teams. To find out more about our benefits, visit the Zynga Benefits site.

The pay range for this position in Ontario at the start of employment is expected to be between $119,140 and $169,140 per year. However, base pay offered is based on market location, and may vary further depending on individualized factors for job candidates, such as job-related knowledge, skills, experience, and other objective business considerations.

Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards and eligibility to participate in our 401(K) plan and Employee Stock Purchase Program. Regular, full-time employees are also eligible for a range of benefits at the Company, including: medical, dental, vision, and basic life insurance coverage; 14 paid holidays per calendar year; paid vacation time per calendar year (ranging from 15 to 25 days) or eligibility to participate in the Company’s discretionary time off program; up to 10 paid sick days per calendar year; paid parental and compassionate leave; wellbeing programs for mental health and other wellness support; family planning support through Maven; commuter benefits; and reimbursements for fitness-related expenses. The use of Artificial Intelligence is not being used to screen candidates. The position 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

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

P-225

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in eastern Canada

As a Solutions Architect at Databricks within the Field Engineering org you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge and can drive complex technology discussions which express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customer's needs and build valuable customer engagements and report to the Field Engineering Manager.

The impact you will have:

• You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
• You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
• Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role with expertise in at least one of the following technologies:
• Big data engineering (Ex: Spark, Hadoop, Kafka)
• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
• Fluent in SQL and database technology.
• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
• [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Travel to customers in your region up to 30% of the time.