Top Data Science Jobs

Own analytics for an embedded business unit end-to-end: define problems, set metrics, build reports, run analyses and experiments, surface insights, and drive data-informed decisions and outcomes with product, growth, AI, or partnerships teams.

Embedded within a core business area, you will define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end to impact growth, product, AI/automation, or partnerships.

Embed with a business unit to define problems, design experiments, build metrics and reports, run analyses using SQL/Python, surface actionable insights, and drive data-informed decisions end-to-end.

Embed within a core business area to define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed recommendations end-to-end with product, growth, and operations.

Embedded on a core business team, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions across growth, product, AI, and partnerships.

Use data analytics and machine learning to detect conduct and financial crime risks. Build data pipelines, clean and transform data, develop statistical and predictive models, apply graph/network analytics, produce dashboards and MI, and collaborate with stakeholders and technology teams to improve AML and market surveillance processes.

Design and analyze experiments and causal studies, build retention measurement and predictive models, develop scalable PySpark/SQL data pipelines, create dashboards, and partner with product and growth teams to improve user engagement and retention.

Senior Data Scientist performs data analysis, regression, and machine learning on structured and unstructured data; builds BI dashboards and metrics; manages ETL and analytics processes; ensures compliance; partners with business, IT, and vendors to design data-driven solutions; leads initiatives and mentors others.

Lead data-science and risk-analytics for risk-based review selection. Build, maintain, and operate models, scripts, formulas, and dashboards that rank partner agencies by risk. Aggregate and validate data, compute health scores, visualize findings and trends, support quarterly risk meetings, and maintain the Risk Support Work Plan.

Build and maintain data science models and quantitative measurement frameworks to guide infrastructure decisions (chargers, parking, depots). Analyze infra efficiency and identify improvements. Collaborate cross-functionally with Supply Operations, Product, and Engineering to incorporate business context into model-driven decisions supporting expansion to new territories and cities.

As a Data Scientist, you will perform ETL/data cleaning, develop visualizations, build predictive models, and support AI solution implementation.

The Data Scientist will analyze data for risk and trading in Daily Fantasy Sports, develop predictive models, and monitor real-time data.

Lead decision science initiatives to improve operational efficiency and financial outcomes. Build decision frameworks, attribution and forecasting models, deliver reproducible Python/SQL code, mentor data scientists, and partner cross-functionally to measure and scale impact.

Build, maintain, and improve decision systems and predictive models; explore internal and external data sources; design and run in-market experiments; prototype solutions using modern tools; recommend strategic changes via rigorous analysis; identify and implement advanced analytics methods in a collaborative data science team.

Lead decision-science initiatives to improve operational efficiency and financial outcomes. Design decision frameworks, attribution and measurement strategies, forecasting and monitoring systems. Produce production-quality Python/SQL code, guide other data scientists, and translate analyses into actionable recommendations for cross-functional stakeholders.

Partner with Marketing to analyze customer and campaign data, build segmentation and personalization models, design and evaluate experiments, and develop attribution models. Communicate insights to stakeholders and productionize models using SQL and Python/R to drive acquisition, engagement, retention, and LTV across digital and offline channels.

Develop and maintain predictive pricing, retention, and conversion models using GLMs and advanced analytics; build monitoring tools for rating performance; support rate filings, product pricing analyses, competitor research, and cross-functional collaboration to inform pricing and enterprise risk decisions.

Lead and mentor data science projects using Epic/Cogito and SQL-based tools. Gather requirements, extract and model data, perform statistical analyses, build visualizations and reports, manage stakeholders and project workflows, and standardize team practices and data architecture.

Support forecasting, predictive modeling, and basic machine learning for ticketing, marketing, finance, and operations. Analyze structured and unstructured data, assist with NLP/text analysis, build dashboards and reports, and communicate insights to stakeholders.

Lead Fraud Data Scientist to define ML strategy, build and productionize fraud detection models (including lending fraud), run advanced analyses and A/B tests, mentor the team, integrate ML with rule engines, and create dashboards to monitor fraud KPIs and model performance.

Lead the fraud data science function: define ML strategy, build and productionize fraud detection models, investigate fraud patterns, run experiments, collaborate with Product/Engineering/Risk, and deliver dashboards and monitoring to minimize fraud losses while preserving customer experience.

Lead the fraud data science effort: define ML strategy, build and productionize real-time fraud detection models, investigate fraud patterns with unsupervised and graph techniques, run experiments, collaborate with product/engineering/risk, and maintain dashboards to monitor model performance and fraud KPIs.

As a Data Scientist, you will analyze complex data sets, build machine learning models, and work in a team to provide solutions, ensuring data security and optimization.

The Data Scientist will analyze complex data, build predictive models, and collaborate with teams to innovate technical solutions and optimize processes.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.