Empower, Innovate, Impact!  At Team A-TEK, we EMPOWER people to drive INNOVATION that IMPACTS mission!

A-TEK operates at the intersection of mission and innovation by applying our deep domain expertise across the federal markets. Embracing our digital-first strategy, A-TEK provides enhanced capabilities in application development, digital transformation, enterprise IT, and scientific services. Our solutions are designed to modernize, automate, secure, protect, and enhance the operations of our federal clients, ensuring they stay ahead in a rapidly evolving digital landscape.

Our work is fueled by a passion to serve our clients’ needs and to protect the safety and welfare of Americans. That passion shapes how we nurture our most valuable asset – Our Employees. A-TEK actively cultivates the talent that drives our success and fosters a creative, challenging, and mission-driven work environment for current and future employees.

This position will be responsible for performing non-research molecular testing of samples for potentially containing biological threat agents. Ensures incoming operational, QA, and other sample types are processed while maintaining chain of custody. Prepares reports, answers questions, troubleshoots, and makes recommendations to the supervisor for inclusion in comprehensive reports. Maintains and operates equipment properly and in a safe manner, including performing routine calibrations and adjustments. Performs all procedures in accordance with proper handling and storage of various materials. Additionally, will be responsible for maintaining knowledge and skills related to position and program. Laboratory operations are 7 days a week. Team members take turns with weekends and holidays to ensure results are reported each day. In the event of a public health emergency, extended work hours and alternative shift work may be required to maintain temporary emergency 24/7 operations. Kindly be aware that a pre-employment drug screening is a requirement.

REQUIRED QUALIFICATIONS:

Bachelor's degree from an accredited university in microbiology, molecular biology, or related course work in biological sciences.

REQUIRES at least one year of laboratory bench experience, utilizing PCR, aseptic techniques and experience with biological assays. Laboratory training that is assigned or accompanies an associated course is not considered applicable training

This position supports a federal contract which requires that all employees and job applicants hold a valid Green Card or US Citizenship at the time of application. 

Please note: This position is not eligible for immigration sponsorship. 

Company Overview

We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation.

If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment.

Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark. 

AI Governance Team, Responsible AI/ML Data Scientist

We are seeking a Vice President, Responsible AI/ML Data Scientist on our AI Governance Team who combines technical expertise in Data Science and Machine Learning with a strong advisory lens to help drive trustworthy AI solution development across Accordion's practices. In this role, you will serve as an internal subject matter expert, embedding responsible AI principles and controls across the AI development lifecycle to drive validated, explainable, compliant, and auditable AI solutions. Drawing on your experience with AI policy, regulatory standards, and testing methodologies, you will translate governance requirements into actionable and testable playbooks that teams across the business can apply consistently. This position is critical to co-designing AI solutions with embedded Responsible AI practices aligned to Accordion's AI Governance principles. As Accordion scales AI capabilities across its practice areas, this role will provide the validation rigor and oversight needed to ensure we develop AI solutions our clients and firm can trust.

This position must be based in our New York City, Chicago, or San Francisco office and is a hybrid role with the flexibility to work remotely 2 days a week.

This position is not eligible for immigration sponsorship.

What You’ll Do:

Governance & Technical Standards

• Translate AI governance, regulatory, and compliance requirements into testable operational Responsible AI playbooks with quantifiable standards for transparency, accuracy, fairness, privacy, and accountability — tailored to Accordion's AI solutions and business model
• Develop frameworks and guidance supporting systematic evaluation, testing, and risk mitigation that enable auditability, lineage, and transparent decision records
• Build evaluation frameworks that guide data scientists and engineering teams in developing, testing, and monitoring AI systems requirements; define mitigation strategies, detection methodologies, and acceptability thresholds
• Develop and implement testing principles for bias detection, model robustness evaluation, privacy preservation, and AI/privacy regulation alignment across different AI architectures and data types
• Establish benchmarks and governance processes aligned with industry standards (e.g., NIST AI RMF, EU AI Act, ISO 42001) that enable auditable AI transparency and explainability against applicable regulations and Accordion standards

Testing & Validation

• Collaborate with data science and engineering teams across our AI solution practices to embed responsible AI controls throughout the development lifecycle
• Develop repeatable testing and validation playbooks and evaluation frameworks for use across practice areas
• Pressure test AI solutions for accuracy, reliability, and trustworthiness, including output anomaly detection, logging, and observability mechanisms
• Develop methods to produce model cards and support audit trails for outputs across Accordion's business practice pillars and Client solutions

Cross-Functional Advisory

• Act as the firm's internal subject matter expert on Responsible AI topics including algorithmic fairness, transparency, privacy preservation, safety protocols, and risk mitigation strategies across the AI lifecycle
• Partner with Legal/Privacy/Risk, Technology, and D&A teams to translate regulatory requirements into actionable and measurable controls and governance structures
• Collaborate with teams developing AI solutions on risk-informed design decisions — advising on model selection, testing approaches, and appropriate guardrails
• Establish Responsible AI frameworks and operational playbooks that demonstrate alignment with evolving AI regulations (e.g., EU AI Act, GDPR, CCPA) and sector-specific requirements
• Monitor emerging AI regulations, industry standards, and responsible AI methodologies — translating insights into actionable internal design guidance
• Where applicable, support higher-risk or higher-profile engagements and AI product development where rigorous testing and evaluation of AI solutions is required

You Have:

• 5+ years of hands-on experience in data and ML, including developing, deploying, and evaluating solutions using a range of skillsets (e.g., statistics, machine learning, NLP, data visualization)
• Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Engineering, Statistics, or a related quantitative field
• Proven technical experience in regulated or complex industries with demonstrated collaboration across Legal/Risk/Compliance, Security, and AI/ML engineering teams
• Track record of operationalizing responsible AI through technical development frameworks, testing protocols, and quantitative evaluation that embed fairness, transparency, and accountability into production AI systems
• Strong programming proficiency in Python, R, or similar languages, with experience in ML frameworks and responsible AI tooling
• Understanding of AI and privacy regulations and standards — including EU AI Act, NIST AI RMF, GDPR, CCPA, and ISO 42001 — and the ability to translate regulatory mandates into technical controls
• Exceptional communication skills with the ability to convey complex technical and regulatory considerations to non-technical stakeholders, including leadership and cross-functional teams

Preferred Qualifications:

• Advanced degree (Master's) in Computer Science, Data Science, Statistics, Information Systems, Engineering, or a related quantitative discipline
• Consulting experience at a leading management or professional services firm
• Direct experience working with Legal/Privacy/Compliance teams on AI, data governance, or emerging technology matters
• Familiarity with responsible AI tooling, red teaming platforms, or model evaluation frameworks

You Are:

• Energized by ensuring AI systems that solve complex business challenges are built responsibly — with fairness, accuracy, transparency, and privacy by design embedded from the start
• A cross-functional collaborator who navigates matrixed organizational dynamics, working seamlessly with Legal/Risk/Compliance, Technology/Engineering, and business teams to establish AI principles, governance playbooks, and technical roadmaps
• A clear communicator who can translate AI governance concepts and technical risk findings into language that resonates with non-technical stakeholders and leadership
• A proactive problem-solver who thrives on staying ahead of AI governance expectations and emerging regulations — and can turn frameworks into practical controls
• An adaptive contributor who embraces the pace of consulting, working across diverse sectors and practice areas

The annual salary for this role ranges from: $160,000 to $175,000 + benefits. This role is also eligible for bonuses, based on individual and company performance. Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to, geographic location, skill set, years and depth of experience, education, certifications, cost of labor and internal equity. 

Accordion is an Equal Opportunity Employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.  We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical​​​ condition, pregnancy, genetic information, gender, sexual orientation, gender identity or ​expression, veteran status, or any other status protected under federal, state, or local law.

Please note that as per Accordion policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening and in alignment with our inclusive diversity values. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that Accordion will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.

#LI-HA1

Please note: This position is not eligible for immigration sponsorship. 

Company Overview 

We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation. 

If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment.

Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark.  

AI Governance Team, AI Risk and Operations 

We are seeking a Vice President, AI Risk and Operations on our AI Governance Team who will play a critical role in maturing and scaling Accordion's enterprise-wide AI Governance risk and operations program. In this role, you will serve as an internal governance practitioner and cross-functional advisor, embedding AI governance policies, procedures, and controls across our operating model for internal AI solutions — with the expectation that this scope will evolve to include client-facing engagements over time. Drawing on your experience with AI policy, frameworks, and risk program design, you will translate complex governance requirements into actionable, scalable implementation systems. This position requires seamlessly bridging the gap between cutting-edge AI development and responsible governance, partnering with senior stakeholders across Practices, Technology, Legal, and Emerging Technology to enabling trusted use and development of AI.  

This position can be based in our New York City or Chicago offices and is a hybrid role with the flexibility to work remotely 2 days a week. Ideal candidates should be local to the desired location. 

This position is not eligible for immigration sponsorship. 

What You’ll Do 

Governance & Frameworks 

• Enhance the enterprise AI Risk Management Framework, including AI use case and supply chain inventory management, use case risk classification taxonomies, and risk-tiering mechanisms aligned to internal standards and emerging regulatory expectations 
• Design and operationalize scalable, end-to-end governance processes across the AI lifecycle  
• Build and maintain AI governance playbooks, risk appetite frameworks, and responsible AI standards  
• Identify opportunities to strengthen controls and oversight through process automation, tooling improvements, and governance workflow optimization 

Cross-Functional Collaboration 

• Partner with Legal, Technology, and Consulting Practice Groups to embed explainability, bias mitigation, and ethical AI principles directly into use case development and delivery workflows 
• Manage the firm's AI Governance obligations and processes end-to-end, including supporting AI and related vendor management supply chain   
• Coordinate with Legal teams to ensure AI systems meet applicable jurisdictional and regulatory requirements, including proactive engagement on evolving global AI legislation 
• Facilitate stakeholder working groups, cross-functional governance forums, and executive communications on AI risk priorities, testing outcomes, and documentation requirements 
• Maintain the internal AI risk register and escalate issues through appropriate governance channels 
• Liaise with Technology and Practices to ensure data lineage and quality standards are met for AI solutions 

Monitoring & Oversight 

• Establish, track, and report on key risk indicators (KRIs) for AI systems in partnership with the Responsible AI Data Scientist and AI Governance Lead, across internal and client-facing AI solutions and products 
• Monitor alignment with global AI regulatory frameworks (e.g., EU AI Act, NIST AI RMF) and support responses to regulatory inquiries, audits, or reviews 
• Evaluate risks associated with third-party and vendor AI solutions across the full sourcing lifecycle — including procurement, onboarding, integration, and ongoing performance oversight — and identify operational guardrails and controls 
• Assess design and operating effectiveness of AI controls against internal policy and external standards, especially for AI, privacy, and industry regulations, under Legal's guidance 
• Produce high-quality audit findings reports with clear recommendations for remediation and monitor implementation of agreed action plans 
• Stay current on AI regulation, industry standards, and emerging best practices 

Internal Enablement (Evolving) 

• Support the development of AI Governance updates, training/awareness programs, and culture-building initiatives to embed responsible AI practices across the organization 
• Contribute to Accordion's Trustworthy AI methodology and internal IP development 
• Over time, support client-facing AI governance assessments, risk remediation roadmaps, and responsible AI frameworks as the program matures and scope expands  

You Have 

• Bachelors degree in Finance, Business Administration, or related field  
• 7+ years’ experience in Risk Operations, Privacy Programs, or PMO/IMO, with at least 3 years directly focused on AI governance or oversight - preferably within professional services, consulting, or PE-backed environments. 
• Demonstrated experience leading complex, multi-jurisdictional integrations and/or global expansion programs, with a track record of building and running structured governance. 
• Strong knowledge of AI and privacy regulations and standards — including EU AI Act, NIST AI RMF, GDPR, CCPA, and ISO 42001 — and the ability to translate regulatory mandates into operational controls 
• Strong grasp of AI/ML technical risks (e.g., bias, model drift, robustness) and associated controls 
• Strong familiarity with regulatory and operational considerations relevant to cross-border professional services (e.g., data/privacy, employment, tax, licensing), and the ability to operationalize them into business processes. 
• Exceptional communication skills with the ability to convey complex technical and regulatory considerations to non-technical stakeholders, including leadership and cross-functional teams 
• Comfortable operating in a high-growth, entrepreneurial environment, with a bias toward structure, scalability, and execution discipline. 
• Strong analytical and problem-solving skills  
• AI usage and familiarity required 
• Excellent attention to detail and organizational skills   
• Ability to adapt to changing priorities and work effectively in a dynamic environment   

Preferred Qualifications 

• Experience in Data Risk Management or direct collaboration with AI/ML development teams 
• Familiarity with AI risk management platforms or tools for model monitoring, documentation, and compliance reporting 
• Experience designing training, awareness, or enablement programs focused on AI risk, model governance, or responsible AI practices 
• Certifications in risk, privacy, or compliance (e.g., CIPP, CIPM, CRISC, CRCM) 
• Passion for AI and a desire to build a world-class risk management function  

You Are 

• Energized by building and scaling governance programs that make AI deployment safer, more trustworthy, and more compliant — across a dynamic, fast-moving consulting environment 
• A cross-functional collaborator who navigates matrixed organizational dynamics, working seamlessly with Legal/Risk/Compliance, Technology/Engineering, and business teams — and can drive decision making and ownership across diverse stakeholders 
• A clear communicator who can translate AI governance concepts, regulatory requirements, and risk findings into actionable guidance for business, technical, and executive audiences 
• A proactive problem-solver who thrives on staying ahead of AI governance expectations and emerging regulations, and can turn frameworks into operational reality 
• An adaptive contributor who embraces the breadth and pace of consulting, working across diverse sectors and practice areas 

The annual salary for this role ranges from: $130,500 to $145,000 + benefits. This role is also eligible for bonuses, based on individual and company performance. Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to, geographic location, skill set, years and depth of experience, education, certifications, cost of labor and internal equity.  

Accordion is an Equal Opportunity Employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.  We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical​​​ condition, pregnancy, genetic information, gender, sexual orientation, gender identity or ​expression, veteran status, or any other status protected under federal, state, or local law. 

Please note that as per Accordion policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening and in alignment with our inclusive diversity values. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that Accordion will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity. 

#LI-HA1

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

About Attain

Built for consumers and companies, alike. 

Klover’s engineering team powers one of the fastest-growing fintech platforms in the U.S., supporting over one million active users each month. Our systems process and move more than $1.5 billion annually, enabling real-time access to financial tools, rewards, and services that help people improve their day-to-day lives.

As part of this team, you’ll help design, build, and scale the systems that underpin Klover’s core products and platform. You’ll work on high-impact, production-grade systems that prioritize reliability, security, and performance, and that integrate with a broad ecosystem of internal and external services. The work you do will directly shape how users interact with Klover’s products, access their money, and experience transparent, low-fee financial services.

Klover engineers collaborate closely with colleagues across backend, frontend, data science, and product teams to deliver scalable, high-quality solutions for a rapidly growing user base. You’ll have the opportunity to work with modern technologies and architectures while helping define and evolve the next generation of inclusive, data-powered financial products—building systems and interfaces that emphasize reliability, privacy, and performance at scale.

About the role

Attain is seeking a Senior/Staff Data Scientist to support the growing needs of our suite of B2C financial services. This role will be highly hands-on, focused on building, improving, validating, and deploying predictive models that power consumer decisioning and business optimization across our app portfolio.

You will work on advanced machine learning and statistical modeling problems, including cash-flow based credit decisioning for our earned wage advance product, Klover, as well as consumer behavior modeling, transaction categorization, paycheck detection, fraud scoring, churn prediction, and other high-impact predictive modeling use cases. The ideal candidate combines strong quantitative fundamentals with practical experience building models and analytical systems from scratch.

Attain Office Hybrid Schedule: 

• Chicago, IL: 4 days in-office; 1 day remote

What a typical week might look like

• Hands-on development of ML and statistical models at the core of our EWA product, with a focus on fast, rigorous, and high-quality execution
• Build and improve predictive models across consumer decisioning, consumer behavior modeling, fraud, churn, transaction intelligence, and other business-critical use cases
• Own the full model development lifecycle, including data exploration, feature engineering, model training, validation, deployment, monitoring, and retraining
• Develop reusable modeling pipelines, analytical tools, and production-quality code to support scalable data science work
• Apply strong statistical and mathematical judgment to model evaluation, calibration, robustness testing, and business impact measurement
• Collaborate with data analysts, engineers, product managers, and business stakeholders to deliver ML models with quality, efficiency, and precision
• Identify new areas where data science, predictive modeling, and optimization can improve product and business outcomes

Preferred Qualifications 

• 5+ years of direct experience working as a Data Scientist, Machine Learning Scientist, Model Developer, Applied Scientist, Economist, or similar role on relevant business problems
• Strongly preferred: Master's, or Ph.D. in a STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, Operations Research, or a related quantitative field
• Demonstrated ability to apply critical thinking, causal inference, abstract reasoning, and generalization to complex, ambiguous business and technical problems
• Strong expertise developing, validating, deploying, and monitoring machine learning models in production
• Experience with AI/ML-assisted development tools and MLOps practices, including experience working with large language models (LLMs) or autonomous agents for code generation and model refinement
• Experience with predictive modeling, consumer behavior modeling, risk modeling, credit decisioning, fraud modeling, churn modeling, or other high-impact applied ML use cases
• Solid foundation in statistics, probability, mathematics, and machine learning fundamentals
• Strong Python coding skills, with the ability to build models, pipelines, and analytical tools from scratch
• Strong SQL skills and experience working with large, messy, real-world datasets
• Experience with feature engineering, model evaluation, calibration, monitoring, retraining, and model performance diagnostics
• Experience with cloud computing services or platforms; GCP preferred
• Familiarity with version control, peer code review, and collaborative software development practices
• Demonstrated ability to learn new technologies, applications, and modeling approaches quickly
• Willingness to roll up your sleeves and wear multiple hats across data science, analytics, modeling, and technical execution based on business needs
• Strong written and verbal communication skills, including the ability to explain technical topics to both technical and non-technical audiences

We’re excited to hear from you. 

At Attain, we are passionate about finding people to continuously help us grow our organization. We encourage you to apply, even if your experience doesn’t match every detail of the job description. If we don’t see something that immediately fits, we will keep your resume on file for future opportunities.

Rewards Network is an Equal Opportunity Employer (EOE). We encourage and strongly support workplace diversity.

Rewards Network is an Equal Opportunity Employer (EOE). We encourage and strongly support workplace diversity.

GTreasury, now a Ripple solution, was acquired by Ripple in 2025, marking a significant expansion into the multi-trillion-dollar corporate finance arena.

GTreasury has more than 40 years of experience supporting some of the world’s largest and most sophisticated companies. Integrating its treasury command center into Ripple’s technology stack gives corporates the ability to move, manage and optimize liquidity in real-time, across traditional and digital assets, under one expanded umbrella.

Join us to build the future of corporate treasury and the infrastructure that powers the Internet of Value.

We are seeking an innovative and forward-thinking Staff Data Scientist and Engineer passionate about building a world-class platform through a world-class team. Driving the technical direction the technology, the evolution of team, and the engineering excellence to make magic happen.

What You’ll Do:

• Technical Leader Platform Data team to build a robust, scalable and resilient data platform serving all portfolio applications
• Collaborate with solution teams, product managers, and deliver robust cloud-based Data platform and solutions
• Make decisions on the solution and the design, architecture, and delivery of systems
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community, and evaluating technical design & code
• Active coach and mentor to your team and grow them in their skills
• Drive agile development and analytical methodologies every day
• Strive to continuously improve the operations, processes, methodologies, technology choices, and practices of the team
• Interact with your team, customers, and peers to share information and improve cross-department processes
• Strive for transparency and partnership between our engineers and our business partners
• Engage in concept discussions, and proposed technology solutions, to meet business objectives and influence such decisions
• Work with multi-functional project teams on solution architecture options for design
• Ensure all work meets quality, operational, and architectural standards needed for organizational success
• Participate in the team’s YBIYRI model (you-build-it-you-run-it), which includes participating in their on-call pager rotation.

Who You Are:

• Leadership acumen, first and foremost
• Strong aptitude with software development lifecycle and engineering excellence processes, Agile methodologies, and the ability to project manage moderately sized projects
• Deep data engineering experience in complex distributed systems
• Strong technical acumen which allows you to be responsible for the technical domain
• Hands-on approach and ready to deep dive into code details with the team
• Strong communication, coordination and influencing skills
• Expert in automation with ETL process, data movement with data medallion architecture
• Deep knowledge and experience with languages/frameworks/tooling (Databricks, SQL, Python, PowerShell, C#/.NET, SQL Server, PostgreSQL, Data Lake/Lakehouse, Qlik, Zoho Analytics, Azure PaaS services)
• Expertise with Izenda, SSRS and AWS Data Services a bonus

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

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 the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized 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

Your Responsibilities as a Environmental Scientist 1:

• Collect soil, water, air, and/or building material samples.
• Gather, analyze, and interpret data. 
• Input data into template reports.
• Actively develop your own career growth.

What we're looking for:

• BS in Geology, Hydrogeology, Environmental Science, or other related field.
• 1-3 years of experience with environmental field sampling and data collection.
• Strong technical writing skills, the ability to successfully multi-task, safety awareness, and a good record and understanding of safe work practices.
• 40-hour HAZWOPER certification required.
• Light construction experience/hands-on skills a plus.
• Experience with data management and report preparation.
• Valid driver's license, good driving history and reliable transportation are required.
• Strong communication skills
• Proficiency with Microsoft Office suite.

Why you'll love working with us:

• Medical, dental and vision plan options.
• Company-paid life, short, and long-term disability insurance.
• 401k plan.
• Paid time-off and holidays.
• Cross-training and the ability to work on a variety of projects.
• Other perks and incentives.
• Working with the best and brightest in the industry.
• 2,000+ employee national firm with 70+ locations across the US.

Req IDs: 11310

#LI-GL1

Company Overview

We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation.

If you crave challenging work and are looking to grow, come solve complex issues alongside 1,600+ finance & technology experts in a supportive, collaborative environment.

Backed by premier private equity firms and headquartered in New York with 11 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark. 

Data & Analytics

Accordion's Data & Analytics (D&A) team offers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges.

We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics.

We deliver data and analytical solutions designed to streamline reporting capabilities and enhance business insights across vast and complex data sets ranging from Sales, Operations, Marketing, Pricing, Customer Strategies, and more.

This role can be based in any of our US office locations and is a hybrid role with the flexibility to work remotely 2 days a week. Ideal candidates should be local to the desired location.

This position is not eligible for immigration sponsorship.

About the Role and You

We're looking for a rare combination: a data scientist who thinks like a strategist and a strategist who speaks fluent data. You fall in love with problems and quantify complex situations using math. This isn't a role about building models in isolation—it's about transforming how a business makes decisions, identifies opportunities, and drives growth. You'll be equal parts analyst, advisor, and architect of our strategic direction.

What You'll Do

You'll sit at the intersection of data and strategy, turning complex business challenges into quantifiable opportunities. This means diving deep into our numbers to surface insights that others miss, then translating those insights into actionable growth strategies. You'll work directly with leadership to shape major business decisions, from market expansion and pricing strategy to resource allocation and competitive positioning.
Your day-to-day will involve identifying the right questions to ask before anyone else thinks to ask them, building the analytical frameworks to answer those questions, and presenting recommendations that fundamentally shift how we operate. You'll own strategic initiatives from conception through execution, measuring impact and iterating as you go. You’ll travel to client sites as needed, leading AI assessment and Strategy Engagements.

What We're Looking For

The Strategic Mindset: You naturally think several moves ahead. You understand business models, competitive dynamics, and growth levers. You can walk into a room with executives and hold your own in discussions about market strategy, unit economics, and long-term planning. You've seen how businesses succeed and fail, and you know how to spot the difference.
The Technical Depth: You're genuinely strong in quantitative methods—statistics, predictive modeling, optimization, experimental design. You can wrangle messy data, build robust analyses, and know when a sophisticated model is needed versus when a simple calculation will do. Python, R, SQL are still in your wheelhouse.
The Translation Layer: You can explain complex analytical concepts to non-technical stakeholders without dumbing them down. You know how to build conviction around data-driven recommendations and can defend your methodology when challenged. You make the quantitative accessible and actionable.
The Business Acumen: You understand P&Ls, growth metrics, customer economics, and operational levers. You've worked closely enough with business teams to know what keeps them up at night and how your analyses can help them sleep better.

Requirements

• 5+ years of experience in analytical roles with increasing strategic responsibility
• Strong foundation in statistics, machine learning, and quantitative analysis
• Demonstrated experience influencing business strategy through data
• Track record of identifying and driving growth opportunities
• Excellent communication skills with technical and executive audiences
• Proficiency in modern data science tools and languages
• Understanding of business finance and growth frameworks

Ideal Background

You might come from management consulting with deep analytical chops, strategic roles at high-growth companies, corporate strategy teams with hands-on data work, or data science roles where you've grown into strategic advisory. What matters most is that you've successfully used data to change how businesses operate and grow.

What Success Looks Like

In your first year, you'll have identified three major strategic opportunities we weren't seeing before, built the analytical infrastructure to evaluate them rigorously, and driven at least one to implementation with measurable business impact. You'll have become a trusted advisor to leadership and the person they turn to when facing the company's thorniest strategic questions.

The annual salary for this role ranges from: $145,000 to $195,000 USD + bonus + benefits. Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate, including but not limited to geographic location, skill set, years and depth of experience, education, certifications, cost of labor and internal equity.

Accordion is an Equal Opportunity Employer. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills.  We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical​​​ condition, pregnancy, genetic information, gender, sexual orientation, gender identity or ​expression, veteran status, or any other status protected under federal, state, or local law.

Please note that as per Accordion policy, we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening and in alignment with our inclusive diversity values. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that Accordion will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.

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Senior Data Scientist Consultant, Managed Agent Platform (MAP) – Agent Platform Team P2392 

Summary 

The Agent Platform Team, within AI Enablement at 84.51°, owns and manages the core platforms that power data science and AI across the organization. This role sits on the MAP (Managed Agent Platform) squad and is focused on helping stand up a new, centralized platform that simplifies and accelerates the design, development, deployment, and monitoring of AI agents across the organization. 

The MAP is being built in response to growing demand for a flexible, no-code/low-code solution that enables both technical and non-technical users to build and deploy agents without deep engineering overhead. The platform is early-stage — the team is actively evaluating different platforms and tooling, defining workflows, and establishing standards. You will be joining at the ground floor and helping shape what this platform becomes. 

You will be the bridge between the engineers building/maintaining the MAP and the data scientists and agent builders who will use it. You are not building agents for end-clients. Instead, you ensure the platform works for the people on it — that capabilities are tested, documented, and adopted smoothly, and that practitioner needs make it back to the engineering team in a way that shapes the roadmap. 

You’ll bring hands-on familiarity with the open-source agent ecosystem — including frameworks like LangChain, LangGraph, Google ADK, and OpenAI Agents SDK — and apply that knowledge to evaluate platform capabilities, inform design decisions, and help practitioners understand what’s possible. As the platform matures, you’ll help onboard users, develop best practices, and drive adoption across the organization. 

This is a small, engineer-heavy squad that is standing something up from scratch. Everyone pitches in on a bit of everything. Priorities will shift frequently as the platform takes shape. Success in this role is less about fixed technical expertise and more about comfort with ambiguity, good judgment about where to spend your time, and the ability to influence without direct authority. 

Responsibilities 

• Voice of the practitioner: Serve as the primary liaison between data scientists and agent builders and the MAP engineering team. Gather requirements, surface pain points, and translate practitioner needs into actionable feedback that shapes platform decisions, standards, and the roadmap. 

• Platform evaluation & definition: Help evaluate and select platform tooling and contribute to defining core platform capabilities — including agent building workflows, orchestration patterns, tool/API connectivity, observability and tracing, evaluation frameworks, and governance controls. Test and document findings, recommended use cases, limitations, and rollout considerations. 

• Onboarding & enablement: As the platform matures, write guides, maintain documentation, lead training sessions, and run office hours to help data scientists and agent builders adopt the MAP. Serve as a first line of support when teams hit roadblocks. 

• Adoption & communication: Evangelize the MAP to increase awareness and drive adoption across the organization. Produce clear communications and materials for both technical and non-technical audiences. 

• Cross-functional collaboration: Work closely with engineers, the solution architect, and product lead on the squad to ensure platform capabilities have well-defined use cases and that guidelines and best practices are established. Act as an agent-building ambassador to cross-functional teams, explaining recommended workflows and the reasoning behind platform choices. 

• Governance & compliance support: Help validate that platform capabilities meet enterprise requirements around security, compliance, observability, scalability, and data governance. 

Qualifications & Experience 

• Bachelor’s degree in mathematics, statistics, computer science, economics, or a related discipline. 

• 2–4 years of experience in data science, AI/ML development, or applied analytics. 

• 2–4 years of experience in tech consulting, retail analytics, or related professional services. 

• Hands-on experience with Python and SQL. 

• Hands-on experience with one or more agent frameworks (e.g., LangChain, LangGraph, Google ADK, OpenAI Agents SDK, CrewAI, AutoGen) is required. 

• Experience gathering user needs, documenting requirements, and driving issues to resolution with technical teams. 

• Experience partnering with software engineering and/or product management teams. 

• Familiarity with LLMs, prompt engineering, and agentic AI concepts. 

• Exposure to agent platforms is a strong plus. 

Skills 

• Strong written and verbal communication, including the ability to explain technical concepts clearly to non-technical audiences and produce high-quality documentation. 

• Ability to influence across teams and seniority levels without direct authority. 

• Comfort operating in ambiguity — this platform is early-stage, and priorities will shift frequently as the team learns what works. 

• Strong project and time management skills; able to manage multiple priorities with minimal oversight. 

• Deep curiosity about the agentic AI ecosystem and a genuine desire to become a subject matter expert on agent orchestration, evaluation, observability, and deployment patterns. 

• Comfort working on a small, engineer-heavy team where you are often the only non-engineer voice in the room. 

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Lead Data Scientist, Relevancy Sciences Data Science & Research – Personalization & Loyalty Strategy (P3764)

Relevancy Sciences Team is responsible for powering relevant, personalized, and scalable customer experiences across Kroger’s e-commerce ecosystem. We build and evolve the science behind search and recommendations that serve millions of customers and support high-scale digital experiences.

We are seeking a Lead Data Scientist to provide technical leadership across search and recommender systems, with a strong focus on modern model architectures, and production-ready machine learning. This role is ideal for someone who combines depth in applied machine learning with strong systems thinking, cross-functional influence, and contributes towards agentic capabilities.

What does the role entail? (Responsibilities)

Technical Leadership, Ownership, and Influence. Own and drive technical initiatives across search & recommender systems. Define and evolve the science strategy for improving content discovery, relevance, personalization, and decision support across digital experiences. Identify high-impact opportunities, make clear technical tradeoffs, and guide the team towards scalable, practical solutions. Rapidly prototype and validate new ideas to accelerate adoption and demonstrate measurable value.

Develop innovative search & recommender systems. Design and build ML solutions tailored to the unique needs of grocery retail domain. Lead the development of systems that improve product discovery and personalization across customer journeys. Bring strong technical and thought leadership on next generation personalization, including the use of Generative AI and agent-based approaches.

Evaluate and improve ML performance. Establish rigorous evaluation methodologies to assess the performance of ML systems across key metrics. Define robust online evaluation frameworks, and guide experimentation strategies that connect model improvements to customer and business outcomes.

Model serving and deployment. Partner closely with Engineering to build and deploy production-ready ML systems. Influence design decisions related to real-time inference, feature access, system integration, monitoring, and reliability. Ensure solutions meet latency, scalability, and operational requirements. Contribute to the evolution of serving and deployment strategies.

Cross-functional leadership. Work closely with Product, Engineering, and business stakeholders to translate needs into clear problem statements, hypotheses, and execution plans. Drive alignment across teams and influence decisions through clear communication of tradeoffs, risks, and expected outcomes.

Mentoring and knowledge sharing. Mentor data scientists and lead technical reviews to improve model quality, experimentation rigor, and systems thinking. Promote best practices in reproducibility and evaluation. Contribute to building a strong, learning-oriented team culture.

What skills and experience do you need? (Requirements)

• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 6+ years of experience applying machine learning to real-world problems with strong experience in search and recommender systems. Strong understanding of approaches such as embeddings and multi-stage decision systems.
• Strong proficiency in Python and SQL, with experience working on large-scale data using tools such as Spark.
• Experience with modern machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Strong foundation in statistics, experimentation, and data analysis, including design of experiments and A/B testing.
• Familiarity with large language models, foundation models, and emerging AI capabilities, including where they are applicable and where they are not.
• Experience evaluating or prototyping GenAI-based solutions is preferred.
• Experience partnering with engineering teams to deploy and maintain machine learning systems in production.
• Understanding of real-time systems, model serving, feature pipelines, and monitoring.
• Ability to make practical tradeoffs between model complexity, performance, latency, and scalability.
• Demonstrated ability to lead technical work across projects and influence direction across data science, engineering, and product teams.
• Experience mentoring or guiding other data scientists and contributing to a strong technical culture.
• Experience working with cloud platforms such as GCP or Azure.
• Experience in retail, e-commerce, or high-scale consumer domains is a plus.

Why join our team? (Rewards)

Impact millions of people. As a member of our data science team, you will have the opportunity to make a tangible difference in the lives of millions of customers by delivering relevant and personalized recommendations that enhance their grocery shopping experience. Your work will directly contribute to increasing customer satisfaction and loyalty, driving business outcomes for our company.

Continuous learning and development. Challenge yourself. We are committed to fostering a culture of continuous learning and development. You will have access to resources and support for expanding your knowledge and skills in cutting-edge technologies, including recommender systems, machine learning and artificial intelligence. Our team encourages exploration and experimentation, providing opportunities to stay at the forefront of industry advancements.

Work on new developments in recommender systems. Join a team at the forefront of innovation in recommender systems and AI. You will have the chance to contribute to pushing the boundaries of what’s possible in personalized recommendation technology. You will have the chance to work on exciting projects that leverage the latest developments in deep learning architectures and data science methodologies.

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Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States and with the Kroger Family of Companies (i.e. H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant status)

You will be joining a team of data scientists operating within the PL&S at 84.51°. Our team partners across multiple portfolios, including Our Brands, Kroger Personal Finance, and the Kroger Enterprise Marketing organization, to support media strategy & execution, targeting, measurement, and enterprise level marketing initiatives.

We work closely with the Our Brands and Kroger Personal Finance teams to plan, execute and measure targeted media and deliver insights that drive growth and efficiency. The team leads the execution of brand loyalty mailers for the Big 3 Our Brands, with a focus on rewarding high‑brand‑loyal households that drive the greatest business value. We also collaborate with Kroger Marketing to execute and measure activations across a range of initiatives, ensuring data driven insights inform business decisions.

Our team is known for being subject matter experts of KPM processes for Kroger Model and owners of a broad set of analytical and external-facing tools. We solve complex client and customer problems by applying the most appropriate statistical and analytic approaches to answer meaningful business questions. In this role, you will be on the front lines supporting Sales and Account Management partners, while also developing deep expertise in retailer data.

You will work hands-on with large-scale retailer databases and leverage the full suite of 84.51° technical and visualization tools, including Python, SQL, Excel, Power BI, and internal platforms, to deliver timely, relevant, and actionable insights. We expect all data scientists on our team to be deeply engaged in advanced analytics and comfortable working directly with data to drive impact.

Responsibilities:  

• Lead end-to-end analytics and data science projects, managing stakeholders and delivering solutions on time, within scope, and to business objectives.
• Develop a strong understanding of the end-to-end CRM (Our Brands Loyalty Mailer) targeting and measurement process to ensure the timely, accurate delivery of mailers and the generation of actionable insights. 
• Apply optimizations and scientific enhancements in targeting to improve customer engagement and maximize ROI.
• Partner closely with Sales and Account Management to own the analytic relationship for OB, driving engagement and shaping analytical offerings through feedback and insight.
• Translate complex first-party data into clear, actionable customer stories and recommendations that inform media strategy, optimization, and business decisions.
• Drive continuous improvement through stronger measurement methodology, increased automation, and clearer data visualization that leads to more actionable insights.
• Attain deep expertise in 84.51° and KPM data assets, measurement techniques, QA processes, and analytic capabilities, confidently applying them to internal and external business needs.
• Collaborate across data science, product, engineering, and capabilities teams to validate new use cases, assess data quality, and support innovation.
• Mentor and support junior data scientists through onboarding, coaching, and knowledge sharing, while championing best practices across the data science community.

Qualifications, Skills and Experience: 

• Bachelor’s degree in statistics, mathematics, business analytics, economics, marketing, or related discipline.
• 2+ years of experience in retail, ad technology, digital media, and/or advertising analytics.
• 2+ years of experience in data science, ad technology, digital media, and/or advertising analytics.
• 2+ years of experience in extracting insights from large databases, translating market research into actionable solutions and presenting findings and recommendations to clients.
• 2+ years of experience using advanced algorithms, programming languages (Python, SQL), or technologies in the development of technical analytics solutions, capabilities, and ad hoc analyses.
• Experience working cross-functionally to continuously improve existing solutions based on client feedback and validated demand.
• Strong interpersonal and communication skills including excellent verbal, written, presentation, and consultation skills.
• Comfortable conveying complex data science techniques and methodological approaches to less technical audiences – both internal and external.
• Strong analytical, problem-solving and decision-making skills.
• Strong data visualization and business acumen skills to link analysis to business impact (grocery and/or retail experience is a plus).
• Natural curiosity that welcomes and embraces ambiguity and change, with a willingness to try new things and to fail.
• Excellent attention to detail, organization skills and ability to work in a collaborative environment.

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• Develop and refine proprietary models to assess customer credit profile
• Collaborate closely with the Strategy and Operations team to drive new initiatives
• Design and implement A/B testing frameworks to evaluate the performance of our models and product configurations, analyzing outcomes to drive continuous improvement
• Communicate insights and recommendations to senior management, providing a data-driven perspective on customer risk and product development strategies

• Degree in Statistics, Mathematics, Economics, Computer Science, or a related field
• 3+ years of experience in Data Science, Analytics or related field
• Advanced programming skills and the ability to write customized programs for meaningful data analysis and predictive modeling (Python)
• Experience working with relational databases, such as SQL
• Excellent knowledge in applied statistical methods and machine learning models
• Ability to improve your work flow and delivery timelines with AI tools.
• Strong problem-solving skills and the ability to work independently in a fast-paced, dynamic environment
• Experience in financial services, fintech, or a related industry preferred

Compensation:

The budgeted annual salary range for this position is $87,000 to $110,000. Actual annual salary will be determined based on qualifications, skills, experience, and level assessed during the hiring process and may fall outside of the range shown. Additional compensation for this role may include a bonus. All full-time employees are eligible to participate in Company benefits, described in more detail here.

Senior Data Scientist Consultant, SPI – Agent Platform Team

Summary

The Agent Platform Team, within AI Enablement at 84.51°, owns and manages the core platforms that power data science and AI across the organization. This role sits on the SPI (Science Platform Innovation) squad and is focused specifically on the Databricks environment and its evolving AI/ML capabilities.

You will be the bridge between the engineers building and maintaining our Databricks platform and the data scientists who use it every day. You are not building models for end-clients. Instead, you ensure the platform behaves as expected for the people on it—that new capabilities are tested, documented, and adopted smoothly, and that practitioner pain points make it back to the platform team in a way that shapes the roadmap.

You’ll build deep familiarity with Databricks’ infrastructure and AI powered capabilities —including Genie Code, Genie spaces, Agent Bricks, MLflow, and other features as they emerge—as well as the Unity Catalog governance layer that underpins them. You’ll test and evaluate new Databricks features and relevant third-party integrations from the perspective of an end-user, document your findings, and help the team decide what to adopt, how to roll it out, and what to skip.

This is a small, highly collaborative squad. Everyone pitches in on a bit of everything. Priorities shift frequently as the Databricks roadmap evolves. Success in this role is less about fixed technical expertise and more about comfort with ambiguity, good judgment about where to spend your time, and the ability to influence without direct authority.

Responsibilities

• Voice of the practitioner: Serve as the primary liaison between data scientists using Databricks and the platform engineering team. Gather requirements, surface pain points, and translate practitioner needs into actionable feedback that shapes platform decisions and roadmaps.
• Technology evaluation: Lead the testing and evaluation of new Databricks capabilities (e.g., Mosaic AI features, Model Serving enhancements, Genie, new Unity Catalog functionality) and relevant third-party tools. Document findings, recommended use cases, limitations, and rollout considerations. Over time, this may evolve from hands-on beta testing toward designing and coordinating evaluation efforts across groups of practitioners.
• Onboarding & enablement: Write guides, maintain documentation, lead training sessions, and run office hours to help data scientists adopt new platform capabilities. Partner with Learning & Development where appropriate. Serve as a first line of support when teams hit roadblocks.
• Adoption & communication: Evangelize Databricks capabilities to increase awareness and drive adoption. Produce clear release notes, communications, and materials for both technical and non-technical audiences.
• Cross-functional collaboration: Work closely with the solution architect, cloud engineer, and product senior on the squad to ensure proposed technologies have well-defined use cases and that guidelines and best practices are established. Act as a data science ambassador to cross-functional teams, explaining recommended workflows and the reasoning behind platform choices.
• Governance & compliance support: Help validate that new platform capabilities meet enterprise requirements around security, compliance, observability, and data governance (e.g., Unity Catalog lineage, Azure connectivity).

Qualifications & Experience

• Bachelor’s degree in mathematics, statistics, computer science, economics, or a related discipline.
• 2–4 years of experience in data science, AI/ML development, or applied analytics.
• 2–4 years of experience in tech consulting, retail analytics, or related professional services.
• Hands-on experience with Python, SQL, PySpark and Databricks
• Experience gathering user needs, documenting requirements, and driving issues to resolution with technical teams.
• Experience partnering with software engineering and/or product management teams.
• Familiarity with LLMs, prompt engineering, or agentic AI concepts is a strong plus.
• Experience with the Databricks ecosystem (Unity Catalog, MLflow) is a strong plus.
• Exposure to agent frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) is a plus.

Skills

• Strong written and verbal communication, including the ability to explain technical concepts clearly to non-technical audiences and produce high-quality documentation.
• Ability to influence across teams and seniority levels without direct authority.
• Comfort operating in ambiguity—priorities shift frequently, and you need good instincts about where to focus.
• Strong project and time management skills; able to manage multiple priorities with minimal oversight.
• Curiosity and enthusiasm for emerging AI technologies and a genuine desire to become a subject matter expert on the Databricks platform and its AI capabilities.

#LI-SSS

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

The quantitative trading teams at Jump Trading probe and examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis, machine learning and deep learning skills, using the results of their research to make forecasts and develop profitable predictive trading models.

What You’ll Do: 

We are seeking research scientists with a demonstrated ability to apply deep learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.

Other duties as assigned or needed.

Skills You’ll Need:

• 5+ years of experience in developing DL systems with measurable impact in industry and/or academia
• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
• Proficiency in Python and/or C++
• Strong foundation in mathematics and statistics
• Ability to thrive in a collaborative, team-oriented environment
• PhD, or Master's degree in Computer Science, Mathematics, (or related subject)
• Strong publications record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent
• Reliable and predictable availability
• Excellent written and verbal communication skills in English

Senior Data Scientist / P3358

Summary

We are seeking a Senior Data Scientist to join our Proprietary Models team. In this role, you will play a critical part in developing, evaluating, and democratizing our foundation models portfolio—including embeddings, pre-trained LLMs, and fine-tuned language models. You will build and optimize embedding pipelines, design rigorous evaluation frameworks, drive models from experimentation to production, and guide business stakeholders through the process of integrating these models into their workflows. The ideal candidate combines deep technical expertise in machine learning and AI with strong problem-solving abilities, a commitment to engineering excellence, and a passion for enabling others to leverage AI effectively.

Responsibilities

Your work will cover a lot of ground, from engineering data pipelines to testing novel AI methodologies to guiding business stakeholders. You will be expected to flex between these skill domains as work progresses through its lifecycle, and to collaborate within a team to make it all happen.

• Develop and optimize embedding pipelines for vector search, retrieval-augmented generation (RAG), and downstream ML applications.
• Conduct rigorous model testing, evaluation, and validation against quality metrics, performance benchmarks, and reliability standards prior to release.
• Design and execute proof of concepts to demonstrate feasibility for specific business problems.
• Build and maintain automated testing frameworks for model performance, data quality, and pipeline integrity.
• Collaborate with MLE/Researchers/Engineers to develop, fine-tune, and deploy foundation models.
• Perform exploratory data analysis (EDA), feature engineering, and data preprocessing to support model development.
• Develop and maintain Jupyter notebooks, scripts, and workflows for reproducible experimentation and analysis.
• Contribute to building and maintenance of code packages, APIs, hosted applications, and other foundation model delivery mechanisms.
• Troubleshoot integration challenges and provide technical guidance for model integrations.
• Guide business stakeholders, data science and engineering teams through adoption and integration of foundation embedding and generative AI models.
• Create documentation, user guides, and best practices for internal model adoption and usage.
• Serve as a liaison between the Foundation Models team and business stakeholders, gathering feedback to inform the development roadmap.

Qualifications and Experience

Required

• Bachelor’s degree in Data Science, ML, Computer Science, or a related discipline
• 3+ years of hands-on experience in data science or machine learning roles
• 3+ years’ experience building in Python using big data tools (e.g. Hadoop, Databricks)
• Hands-on experience building processes incorporating LLMs, embeddings, or related model architecture
• Experience applying embeddings within AI projects and machine learning applications
• Track record of shipping, measuring, and maintaining machine learning models in production
• Exceptional communication skills with ability to explain complex technical concepts to non-technical audiences
• Experience in stakeholder management, technical documentation creation, and cross-functional collaboration

Preferred

• Experience building in cloud data platforms (i.e. Azure, GCP)
• Previous developer relations, technical evangelism, or advocacy experience
• Background in NLP, conversational AI, or generative AI applications
• Open-source contributions or thought leadership in AI/ML community

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SENIOR DATA SCIENTIST (P2408)

SUMMARY:

The Core Science team is responsible for some of our most foundational data science products including enterprise-wide segmentations and store measurement tools. As Senior Data Scientist on the Core Science team, you will build and maintain our new Customer Dimensions and Functional Loyalty. Our team plays a crucial role in building core segmentations that are used across the business in various functions like customer reporting and targeting.

In this role, you will maintain and enhance existing dimensions, support business use of dimensions, build and monitor data quality dashboards, and develop new customer dimensions to expand our view of customers. This includes responding to time-sensitive requests for deep-dive analyses, managing routine processes, and innovation of new segmentations.

You will leverage a diverse technical toolkit including Power BI for dashboard development, GitHub for code management and version control, and PySpark for programming. Additionally, you'll have opportunities to explore the use of embeddings and incorporate AI technologies to enhance our analytical capabilities and create more efficient solutions.

Success in this role requires strong analytical skills and business insights combined with intellectual curiosity and adaptability. We're looking for someone who embraces change, demonstrates enthusiasm for learning new methodologies, and can balance maintaining existing systems while innovating for the future.

RESPONSIBILITIES:

• Effectively managing projects, tasks and stakeholders to ensure that projects are delivered on time, within budget and to brief specification while ensuring minimal downtime and maximum utilization.
• Interpreting results and developing actionable recommendations from the data analysis to build relevant customer stories for clients.
• Identifying and implementing artificial intelligence solutions to enhance business processes, drive operational efficiencies, and deliver increased value to stakeholders.
• Quality Assurance of own code and that of team members to ensure the highest quality work is being delivered to our clients.
• Identifying opportunities for standardization & automation of existing solutions and processes to enable 84.51° to realize the maximum potential from our teams.
• Challenging and improving 84.51° analytical capabilities/products.
• Working closely with key internal stakeholders to ensure sound knowledge of client objectives and customer insight, to subsequently design best-in-class solutions.

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• 2+ years of experience in consulting or professional services
• 2+ years of experience in extracting insights from large databases, translating market research into actionable solutions and presenting findings and recommendations to clients
• 2+ years of experience using advanced algorithms, programming languages, or technologies in the development of technical analytics solutions or capabilities.
• Experience querying data from relational databases using SQL.
• Experience using R, Python, or other similar statistical software to develop analytical solutions.
• Experience with data wrangling, data cleaning and prep, dimensionality reduction.
• Experience with Big Data concepts, tools, and architecture (e.g. Hadoop, Pig, Hive, Spark, Sparkling Water).
• Ability to create computationally efficient solutions.
• Strong academic background in mathematics, statistics, computer science, economics, or similar discipline.
• Data visualization skills and ability to present technical solutions to non-technical audience.
• Strong interpersonal and communication skills.
• Strong analytical, creative problem-solving and decision making skills
• Strong business acumen; grocery and/or retail experience is a plus.
• Passionate about data, analysis and insights.
• Natural curiosity that welcomes and embraces change and willingness to try new things and to fail, particularly in exploring emerging technologies and AI applications.
• Ability to work in a highly collaborative environment.

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About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role

Data Scientists bridge the gap between raw data and predictive modelling. We believe everything starts with data. You will work closely with our quantitative research team, applying advanced techniques to engineer, validate, and refine features that feed directly into our systematic models. This is a role within an established investment team, offering opportunities for progression into more senior research responsibilities across the full trading pipeline.

Responsibilities

• Conduct thorough data analysis under the mentorship of a senior quantitative researcher.
• Generate novel ideas for enhanced proprietary data products.
• Track and evaluate new offerings from internal and external data vendors in partnership with Compliance.
• Transform firm approved raw datasets into robust features for our systematic models.
• Build analytical tools to supplement our shared research framework.

Requirements

• BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline.
• Programming in Python (or a comparable language) and working knowledge of SQL.
• Strong analytical and quantitative skills.
• Willingness to take ownership of their work.
• Ability to work both independently and collaboratively within a team.
• Strong desire to deliver high quality results in a timely fashion.
• High attention to detail.
• Prior experience as a data analyst, data sourcing specialist, or data scientist for a financial firm is a plus
• Commitment to the highest ethical standards.

We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas or take over sponsorship at this time.

About the role:

As a Data Scientist, you will be one of Enova’s most valuable team members. You will develop, enhance and test the company’s models for use in determining the appropriate lending criteria and verification procedures. You will perform independent model validations to evaluate model fit for purpose, conceptual soundness, mathematical theory and assumptions, data/assumptions, and output reasonableness. At times, you may be asked to conduct ad hoc analysis using statistical and financial tools to recommend for risk management, marketing and operational strategies. You will demonstrate the ability to interpret and organize data, and communicate it effectively to cross functional teams to solve business problems, provide requirements and support implementation.

Responsibilities:

• Perform model validation of credit risk models
• Prepare model validation reports and write technical documentation
• Assist analysts in validating and preparing their models for production
• Interact with model stakeholders and business partners to gather information about credit models and risk acceptances
• Support model releases to ensure they are quickly and accurately put into production
• Monitor model performance dashboards, build alerts, and escalate concerns as appropriate
• Support and improve automated model training processes by using data manipulation, and machine learning skills
• Use your programming skills to develop and test programs for custom tool development

Requirements:

• Experience in developing advanced credit risk models
• 3+ years of experience in quantitative analysis in the financial services industry is preferred but not required
• Knowledge of statistical models in risk management
• Advanced programming skills in Python and the ability to write customized programs for meaningful data analysis
• Experience working with relational databases, such as SQL

Compensation:

The budgeted annual salary range for this position is $87,000 to $110,000. Actual annual salary will be determined based on qualifications, skills, experience, and level assessed during the hiring process and may fall outside of the range shown. Additional compensation for this role may include a bonus. All full-time employees are eligible to participate in Company benefits, described in more detail here.