Data Scientist

• Lead development and advancement of ML models for bidding, targeting, and marketing optimization across paid search, lead aggregators, affiliates, direct mail, and emerging performance channels
• Partner with Lifetime Value, Engineering, Marketing, and external vendors to translate business opportunities into scalable ML solutions
• Set the technical direction of the Performance Marketing team by building and prioritizing a multi-quarter research roadmap spanning modeling, experimentation, and ML operations
• Identify and frame high-leverage opportunities across performance marketing, evaluate technical approaches, and prioritize investments
• Mentor data scientists and MLEs in research design, ML model development, technical decision-making, and production engineering practices
• Design and build production-ready ML systems with maintainable code, reproducible research, automated testing, deployment, and operational reliability
• Build monitoring frameworks for interconnected ML systems to detect model degradation, data issues, and channel performance changes
• Lead zero-to-one prototypes and introduce new modeling or ML operations capabilities
• Engage regularly with cross-functional departments and the executive team

Staff Data Scientist optimizing Root’s car-insurance performance marketing with machine learning

Staff Data Scientist I, Direct Marketing

Staff Data Scientist leading bidding, targeting, and marketing optimization for Root’s technology-driven car insurance business. Building production ML systems and guiding performance marketing strategy.

• Own ambiguous, high-impact problem spaces across product and business domains, from question framing through analysis and solution development with cross-functional partners
• Partner with cross-functional stakeholders and company leadership to shape product strategy and anticipate future challenges
• Design and evaluate experiments to measure the impact of product and strategic changes
• Analyze product data to uncover root causes of metric movements
• Develop tools, methodologies, and frameworks that improve data practices across the data team and company
• Mentor other data scientists and instill industry best practices
• Devise measurements and metrics, design randomized controlled experiments, build visualizations, and uncover usage patterns and opportunities across Quora
• Work on domains including user growth, content quality, monetization, personalization, marketplace dynamics, and long-term company strategy

Staff Data Scientist shaping experiments and product strategy for Quora’s knowledge platform

Staff Data Scientist

Staff Data Scientist analyzing Quora’s knowledge-sharing product through experimentation, metrics, and modeling. Influencing product strategy across growth, personalization, content quality, and monetization.

• Lead client engagements at the intersection of data science, AI, and strategy
• Own projects from scoping through delivery
• Collaborate with clients and cross-functional teams to solve complex marketing challenges
• Apply advanced analytics, modeling, statistics, measurement, and experimentation techniques
• Manage, mentor, and grow analysts and data scientists
• Advise quantitative survey researchers
• Foster innovation, collaboration, and continuous learning
• Ensure delivery of high-quality work
• Pitch new projects and grow client relationships
• Track marketing analytics trends and introduce new methodologies, tools, and techniques
• Advise clients and team members on experimentation, machine learning, and advanced data science methods

Director of Data Science leading AI-driven marketing analytics at Known, a data science and creative agency

Director, Data Science

Director of Data Science leading AI-driven marketing analytics and client engagements at Known, a data science and creative agency. Managing data science teams and driving strategic growth.

• Perform data manipulation and cleaning
• Build regression models
• Deliver insights to senior leadership to support profitable sales and long-term strategies
• Contribute to projects involving sales forecasting, personalization recommendations, store profitability, and A/B testing
• Create dashboards and reporting for Finance, Marketing, Digital Experience, Store Operations, and IT
• Provide real-time, data-driven insights to business partners
• Collaborate with business partners on ad hoc analyses
• Ensure business questions receive accurate and informed responses
• Learn how Data Science is used in a corporate retail setting

Data Science Co-op applying analytics and modeling to optimize TJX’s off-price retail business

Data Science Co-op

Data Science Co-op supporting TJX’s off-price retail business through SQL, Python, modeling, forecasting, dashboards, and data-driven analysis.

• Perform data cleaning and transformation
• Train and evaluate statistical and machine learning models
• Translate model outputs into meaningful findings and deliver insights that influence business processes and deepen customer understanding
• Create dashboards and build reporting for Customer Insights, Marketing, Digital/eCommerce, Store Operations, Loyalty, and Finance partners
• Collaborate with business partners on ad hoc analyses
• Provide accurate and informed responses to business questions
• Support data science efforts that improve marketing effectiveness, customer value, and customer engagement across TJX brands in stores and online

Data Science Co-op improving marketing insights for TJX’s off-price retail brands

Data Science Co-op, Consumer Insights

Data Science Co-op supporting TJX’s off-price retail brands through customer analytics, machine learning, dashboards, and marketing effectiveness insights.

• Perform sophisticated statistical and predictive analytics and machine learning modeling to provide actionable insights
• Provide consultation to business leaders and stakeholders on leveraging analytics insights and developing analytics strategies
• Independently perform data analytics using econometrics, machine learning, neural networks, and natural language processing on structured and unstructured data
• Produce data visualizations to communicate insights and influence outcomes
• Own end-to-end data science solution design, technical delivery, and measurable business outcomes
• Engage stakeholders to identify business objectives and scope solution requirements
• Write, document, and deploy custom code in Python, SAS, R, and other environments to create predictive analytics applications
• Use, maintain, share, and collaborate through Truist internal code repositories
• Research and advocate adoption of emerging data science methods and technologies
• Apply risk management practices and collaborate on data usage, governance, and analytics capabilities

Data Scientist I applying machine learning and predictive analytics at Truist Financial

Data Scientist I

Data Scientist I applying statistical modeling, machine learning, and predictive analytics at Truist Financial. Delivering data-driven insights, visualizations, and solutions for business outcomes and risk management.

• Design and execute rigorous experimental frameworks
• Lead the transition from manual analysis to automated, scalable solutions integrated with the Netflix Experimentation Platform
• Define best practices for trustworthy decision-making at scale
• Advance and implement biddable media models and dynamically priced auctions
• Develop strategies to optimize marketplace mechanics while balancing supply, demand, and member experience
• Partner with Product and Engineering to solve cold-start measurement challenges
• Scale the ad platform across diverse international markets
• Act as a high-level consultant to Product, Strategy, and Engineering teams
• Identify research opportunities, quantify potential business impact, and advocate for resource allocation
• Cultivate partnerships with product, engineering, operations, design, and consumer research stakeholders
• Deliver end-to-end solutions using causal inference, machine learning, and data exploration
• Maintain high standards for documentation and reproducibility

Data Scientist architecting ad experimentation and auction models for Netflix’s global streaming marketplace

Data Scientist 5 – Ads Experimentation

Data Scientist architecting experimentation, causal inference, and auction models for Netflix’s global advertising marketplace. Scaling measurement and marketplace mechanics across international markets.

• Analyze entities across the Plaid network to understand behavior and identify opportunities, anomalies, and risks
• Create foundational metrics, dashboards, and monitoring systems for network health and machine learning model performance
• Evaluate the value and performance of machine learning models using customer and internal data
• Identify opportunities to improve existing models and translate findings into actionable narratives for product and engineering leaders
• Design experiments, define success metrics and guardrails, analyze results, and communicate recommendations to stakeholders
• Analyze Plaid product and customer data to identify opportunities for product improvement and expansion
• Partner with cross-functional teams to build reliable data models and analytics workflows
• Establish the analytics and metrics backbone for the Embedded Insights team
• Support machine learning model development and contribute to Plaid network health and product quality

Senior Data Scientist improving machine learning and financial connectivity products at Plaid

Senior Data Scientist – Embedded Insights

Senior Data Scientist establishing analytics and metrics for Plaid’s financial connectivity network. Evaluating machine learning models and guiding product improvements through experimentation.

• Design, implement, evaluate, and help deploy machine learning models for bidding, pacing, KPI prediction, and forecasting
• Analyze large-scale behavioral and performance data using Spark, Scala/PySpark, SQL, and Python
• Navigate and improve complex legacy codebases
• Collaborate with product managers, engineers, and other data scientists to define problems and deliver end-to-end solutions
• Write clear, concise technical documentation
• Communicate insights effectively to technical and non-technical stakeholders
• Work on optimization and bidding logic for the Nexxen Demand-Side Platform
• Improve bidding, impression-winning, and optimization performance across real-time programmatic advertising exchanges

Data Scientist optimizing Nexxen’s real-time programmatic advertising bidding platform

Data Scientist optimizing machine learning models for Nexxen’s real-time programmatic advertising DSP. Analyzing large-scale data and improving bidding, pacing, and KPI prediction.

• Serve as Capability Area Lead for the Cost Engineering section within EEMS
• Provide technical leadership, direction, and stewardship across the department
• Lead cost engineering and economic analyses, including LCCEs, ICEs, IGCEs, affordability and cost-risk assessments, cost realism and should-cost analyses, source selections, proposal evaluations, acquisition studies, investment studies, and business-case studies
• Provide independent, data-driven advice to government customers and program offices
• Translate complex analyses into insights supporting acquisition, program, investment, pricing, and business decisions
• Advance cost engineering methodologies, models, tools, data practices, standards, and peer-review processes
• Lead and mentor staff and support knowledge transfer
• Collaborate with Schedule Engineering, Operations Research and Management Sciences, and Acquisition Engineering Research sections
• Identify customer needs, develop technical approaches and scopes of work, strengthen relationships, and create cross-capability opportunities
• Support business development and capture through proposals, statements of work, technical volumes, pricing strategies, and customer engagements
• Represent and advance the Cost Engineering profession through thought leadership, research, professional engagement, and collaboration with government, industry, and academia

Cost Analytics Lead Engineer advancing aerospace cost analysis for The Aerospace Corporation

Engineering Economics & Cost Analytics Lead Engineer

Cost Analytics Lead Engineer leading aerospace cost, economic, and affordability analyses for The Aerospace Corporation.
Advising government and commercial space customers while mentoring cost engineering teams.

• Lead governance workstreams and small delivery teams to design and implement actionable, sustainable data/AI governance programs.
• Own client relationships for the workstream by setting expectations, facilitating executive discussions, and driving alignment across business, IT, privacy, security, and legal stakeholders.
• Advise on, present, implement, and operate new Collibra Data Catalog instances.
• Provide hands-on Collibra implementation support, including prioritizing high-value features and scoping work management.
• Design and operationalize governance operating models, including councils, data stewardship models, escalation paths, and integrated controls across data, analytics, and AI.
• Define implementation roadmaps connecting strategy to execution, including sequencing, dependencies, change management, and measurable adoption outcomes.
• Establish AI governance and responsible AI guardrails, including inventories, risk workflows, review boards, documentation standards, third-party oversight, and compliance reporting.
• Institute tactical and functional data governance operations and controls.
• Translate governance needs into scalable enablement through templates, playbooks, training, and communications.
• Support business growth and pursuits through proposal development, scoping, staffing plans, and reusable assets and accelerators.
• Travel as needed based on client and project needs.

Data governance lead implementing Collibra and AI governance programs for Guidehouse consulting clients

Data Governance Lead – Data Catalog

Data governance lead implementing Collibra catalogs and AI governance programs for Guidehouse consulting clients. Leading workstreams, operating models, roadmaps, and executive stakeholder alignment.

• Lead the Sales Analytics team and set its vision across customer acquisition and product expansion sales teams
• Conduct deep-dive analyses to identify revenue drivers and anomalies
• Translate complex data into actionable insights and recommendations for senior leadership and cross-functional partners
• Rebuild foundational data systems with Data Engineering and Service Platform partners
• Align with the Chief Revenue Officer, Sales Operations, Data Engineering, and Service Platform teams on a shared data and infrastructure roadmap
• Evolve sales forecasting methodology using rigorous analytics such as propensity scoring and improved seasonality controls
• Create AI-enabled self-service analytics capabilities for operations partners
• Recruit, mentor, and develop a high-performing analytics team
• Shift the team from reactive query fulfillment toward strategic analysis
• Connect Data Engineering, Analytics Engineering, Data Science, and AI/ML Engineering solutions to revenue-driving analytics

Head of Sales Data Science & Analytics rebuilding Gusto’s revenue data foundation

Head of Sales Data Science, Analytics

Head of Sales Data Science & Analytics leading Gusto’s sales analytics team. Rebuilding revenue data infrastructure and advancing forecasting, causal analysis, and AI-enabled self-service.

• Identify suitable, fit-for-purpose data sources and perform initial data quality checks
• Apply data strategy principles to routine business problems
• Support deployment, evaluation, scalability, and sustainability of analytical models
• Develop and test application features using recommended programming languages and business, technical, and data requirements
• Identify model evaluation metrics and apply testing and tuning techniques to assess accuracy, fit, validity, and robustness
• Create graphical representations of data and model outcomes
• Design data representations for multiple datasets and collaborate with UX designers and UI engineers on front-end applications
• Present data insights to teams and business audiences using appropriate visualization frameworks
• Guide and mentor junior associates on visualization, modeling, and analytics techniques
• Provide recommendations and develop business cases addressing complex business issues
• Translate business requirements into projects, activities, tasks, and domain-specific artifacts
• Formulate business problems into data-related or mathematical solutions
• Select and develop analytical models for complex structured data
• Conduct exploratory data analysis, hypothesis testing, statistical inference, trend analysis, and cluster analysis
• Design experiments, test hypotheses, and provide business recommendations and insights
• Build stakeholder relationships and support implementation of business solutions
• Monitor progress and results, identify improvement opportunities, and adapt to changing demands
• Model compliance with company policies, values, ethics, and standards

Senior Data Science intern developing analytical models and insights for Walmart retail operations

Senior Data Science Intern

Senior Data Science intern developing analytical models, data visualizations, and business insights for Walmart. Supporting data-driven solutions across retail operations and stakeholder teams.

• Apply data strategy principles to routine business problems involving a single function
• Select analytical modeling techniques for structured, complex data
• Conduct exploratory data analysis, statistical analysis, hypothesis testing, and statistical inference
• Define and finalize features and introduce revised features to improve analysis outcomes
• Design and conduct experiments and test hypotheses
• Perform trend and cluster analysis and provide business recommendations and insights
• Mentor and guide junior associates on modeling and analytics techniques
• Support deployment, evaluation, scalability, and sustainability of analytical models
• Develop solution and application features using recommended programming languages
• Test code using recommended testing approaches
• Translate business problems into data-related or mathematical solutions
• Identify appropriate methods and tools to solve technical problems
• Support business cases, recommendations, process updates, and assigned project activities
• Identify suitable datasets and data sources while maintaining awareness of data quality
• Support model fit testing and validation and assess feature impact on performance
• Create graphical representations of data and model outcomes
• Support customer requirements and design data representations
• Present data visualizations and influence the team using business understanding
• Build stakeholder relationships, implement business solutions, and monitor progress and results
• Uphold Walmart policies, values, ethics, compliance, and customer/member-focused practices
• Collaborate cross-functionally and support talent development through feedback, coaching, and mentoring

Data Science III intern developing machine-learning solutions for Walmart retail operations

Data Science Intern

Data Science III intern developing analytical models and machine-learning solutions for Walmart. Supporting experiments, model validation, deployment, visualization, and business recommendations.

• Find and ship predictive signals across student engagement, outcomes, and partner health
• Build predictive models that integrate with partners’ existing systems and drive action
• Set actionable alert thresholds and account for false-positive costs
• Evaluate model performance across student populations and document limitations
• Monitor deployed models for drift and retire models that no longer provide value
• Decide when an analysis, definition change, or conversation is preferable to building a model
• Own scheduling and monitoring for models using maintainable orchestration
• Apply embeddings, clustering, and classification to conversational, support, service, and other unstructured data
• Turn unstructured-data findings into product and partner-experience improvements
• Build text-analysis foundations for retrieval and AI tooling
• Own in-warehouse AI configuration, verified queries, prompts, agent tooling, and semantic views exposing model output
• Build and maintain an AI evaluation framework with precise rubrics, sampling methodology, and improvement reporting
• Set evaluation standards and share methodology with Product and Engineering
• Equip internal teams with reusable data and analysis for strategic partners
• Build tooling and training that enable teams to answer questions independently
• Document reasoning, assumptions, and tradeoffs in the internal data knowledge base
• Work in dbt/code alongside engineers and contribute to shared definitions
• Collaborate with Senior Data Engineer, Senior Analytics Engineer, Product, Engineering, Partner Success, Leadership, and external stakeholders

Senior Data Scientist building predictive models for Mainstay’s college and business engagement platform

Senior Data Scientist

Senior Data Scientist building predictive models and NLP tools for Mainstay, whose platform helps colleges and businesses drive actionable conversations. Owning AI evaluation, data tooling, and production model monitoring.

• Analyze marketing and business performance
• Build models to understand the impact of marketing investments and strategy
• Identify and communicate insights and opportunities to executives and internal teams
• Perform ad-hoc analyses evaluating marketing spend efficiency
• Build reporting infrastructure and make budgeting recommendations to optimize growth
• Integrate event data with surveys, ad publishers, app store data, and other customer data sources
• Support reporting and business intelligence needs of the Marketing team
• Partner with Marketing teams across business units on marketing measurement, A/B test design and analysis, and data-driven insights

Data Scientist optimizing marketing analytics for Match Group’s global dating platforms

Data Scientist, Marketing Analytics

Data Scientist optimizing marketing measurement, experiments, and reporting for Match Group’s global dating platforms. Delivering actionable growth insights across Tinder, Hinge, and other brands.

• Define and lead AI and data science strategy across machine learning, NLP, search, recommendation, experimentation, and generative AI
• Lead and develop high-performing teams through coaching, prioritization, scientific rigor, and inclusive collaboration
• Deliver AI and knowledge-discovery systems across the lifecycle from experimentation through production, including LLMs, RAG, search, and domain-enriched AI solutions
• Establish AI evaluation frameworks, metrics, experimentation practices, and responsible AI standards
• Partner with product, technology, and business leaders to shape roadmaps and align teams on customer and business impact

Manager leading AI and data science teams at Elsevier, advancing healthcare and research information

Manager, Data Science

Manager leading AI and data science strategy at Elsevier, a global information and analytics company. Delivering scalable ML, NLP, search, and generative AI systems for healthcare and research.

• Ensure the organization leverages appropriate data and analyses for change control decisions
• Drive use of process control systems to improve capability, matching, and stability of semiconductor process technologies
• Use predictive modeling, statistics, machine learning, data mining, and other data analysis techniques to extract insights from structured and unstructured data
• Develop software, algorithms, and applications for mathematical data analysis, large-scale experimentation, data-driven applications, and business problem solving
• Assist the business with causal inferences by identifying patterns and relationships in data
• Interface with process and integration functional-area analytics teams
• Partner with Intel's factory automation organization and Foundry TD functional areas to support semiconductor process development and system transfer to the worldwide virtual factory network
• Help develop and support modern AI/ML solutions

Data Scientist/Statistician advancing AI-driven process control for Intel semiconductor foundry operations

Data Scientist/Statistician

Data Scientist/Statistician developing statistical, AI/ML, and data solutions for Intel's semiconductor foundry operations. Improving process control, capability, matching, and change-control decisions.

• Research and evaluate statistical and econometric approaches for Media Mix Modeling and marketing effectiveness measurement
• Develop, test, and enhance MMM algorithms across the full modeling lifecycle
• Work with time-series, panel, and observational marketing data to develop robust models of media response and business outcomes
• Explore media response curves, saturation effects, adstock and carryover effects, incrementality and causal inference, channel interaction and synergies, seasonality, trends, external factors, regularization, variable selection, uncertainty estimation, statistical inference, and Bayesian and frequentist modeling approaches
• Develop model diagnostics and validation frameworks assessing model stability, predictive performance, statistical significance, and business interpretability
• Conduct simulation and experimentation to understand algorithm behavior under different data-generating conditions
• Compare modeling methodologies and identify opportunities to improve model accuracy, robustness, and interpretability
• Translate research findings into production-ready algorithms and analytical workflows
• Work with real client datasets and address practical challenges of applying MMM to imperfect business data
• Collaborate with senior data scientists to document methodology, assumptions, limitations, and results
• Contribute to next-generation MMM capabilities within FocusKPI

PhD Data Science Intern developing Media Mix Modeling algorithms for FocusKPI analytics consulting

PhD Data Science Intern – Media Mix Modeling

PhD Data Science Intern researching Media Mix Modeling algorithms for FocusKPI, an analytics consultancy serving Fortune 500 IT clients. Building validated, production-ready marketing measurement solutions.

• Partner with Product, Engineering, and Design teams and business units to understand users, product performance, and the marketplace
• Work closely with PED to set goals, understand product engagement, and learn from experiments in the two-sided marketplace
• Develop measurement frameworks and establish new metrics or reporting systems
• Align cross-functional stakeholders on priorities and the analytical roadmap
• Design and analyze experiments
• Analyze user behavior and marketplace dynamics
• Investigate business trends and diagnose drivers of business performance
• Collaborate with Analytics, Data Engineering, and the broader data community to grow data culture
• Report directly to the Head of Analytics

Senior Data Scientist analyzing users and marketplace performance for Peerspace’s venue-rental marketplace

Senior Data Scientist partnering with product teams to analyze users, experiments, and marketplace performance. Building metrics and insights for Peerspace’s online venue-rental marketplace.

Data Scientist jobs in United States

See all jobs on JobTailor

Staff Data Scientist I, Direct Marketing

Staff Data Scientist

Director, Data Science

Data Science Co-op

Data Science Co-op, Consumer Insights

Data Scientist I

Data Scientist 5 – Ads Experimentation

Senior Data Scientist – Embedded Insights

Data Scientist

Engineering Economics & Cost Analytics Lead Engineer

Data Governance Lead – Data Catalog

Head of Sales Data Science, Analytics

Senior Data Science Intern

Data Science Intern

Senior Data Scientist

Data Scientist, Marketing Analytics

Manager, Data Science

Data Scientist/Statistician

PhD Data Science Intern – Media Mix Modeling

Senior Data Scientist