Top Data Science Jobs

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

The Data Scientist will develop solutions using AWS, validate data formats, maintain source code in GitHub, and collaborate with teams on collection capabilities.

Lead product-focused data science work: define and track metrics, design and analyze A/B tests, evaluate model and agent performance across conversations and workflows, perform root-cause analyses, build statistical models and dashboards, and partner with Engineering and ML teams to improve instrumentation and data quality.

Lead analytics for new-user activation and early-life product experiences. Design and analyze experiments, partner with product/engineering/design, build data foundations, and recommend product changes to improve user retention and habit formation.

As a Data Scientist, you will leverage data exploration, analysis, and machine learning to provide insights and solutions for clients, using various data sources and tools to address complex challenges.

Lead data science efforts to explore, clean, analyze, and visualize structured and unstructured data. Develop predictive models, NLP/text-mining and machine learning solutions, wrangle data from disparate sources and guide teammates to deliver production-ready analytic solutions for government and commercial clients.

As a Data Scientist, you will analyze data, develop algorithms, and utilize IoT and machine learning to solve complex problems for clients.

Design and deliver data products for DoW by sourcing, cleaning, transforming, and visualizing data. Build dashboards and metrics in WDP, brief senior leaders, and support IT portfolio analytics using Databricks, Tableau/Qlik, SQL, and Python.

Design and implement data science solutions: ingest and clean data, build ETL pipelines, develop predictive models and algorithms, create visualizations, lead teammates, and deliver analytic products for intelligence and commercial clients while maintaining classified clearance requirements.

As a Data Scientist, you'll analyze and interpret complex data sets, develop algorithms, and work with clients to provide actionable insights, utilizing tools from machine learning and AI.

Perform large-scale data analysis and modeling using Hadoop ecosystems and general-purpose languages (Java, Python, R). Apply statistical techniques and machine learning on big datasets, develop creative solutions, visualize patterns, and work independently within a research-oriented team. Strong communication and rapid conceptual learning are expected.

Perform statistical computing using linear programming to identify and extract required data from Oracle databases. Design and write SQL queries to extract and export data, analyze results, and support equity and collateral optimization business needs. Strong communication and database analytical skills required for a 6-month contract.

Integrate and analyze large, disparate datasets using statistical methods and machine learning to generate actionable business insights. Build and validate predictive models, analyze unstructured data, and present findings to stakeholders. Manage project budgets and timelines, and apply industry knowledge to deliver on-time, on-budget analytics solutions.

Perform statistical analysis, predictive modeling, and data visualization on workforce and training data. Build dashboards, produce ad hoc analyses and decision-support products, advise on data governance/privacy, and collaborate with stakeholders to define metrics, deliverables, and reproducible analytic workflows.

As a Data Scientist at Profound, you'll build predictive models, optimize AI-driven brand visibility, and turn data insights into actionable strategies. Requires proficiency in Python, R, and SQL, with 3+ years of analytics experience.

As a Data Scientist at Retool, you will analyze customer behavior and business performance, build analytical models, and provide insights to guide strategy across teams.

The Data Scientist will apply machine learning and statistical analysis to support mission analysis, develop analytical tools, and visualize complex datasets for insights.

The Data Scientist will develop data-driven solutions, integrate APIs, manipulate data using Python, analyze large datasets, and collaborate with teams.

Lead client-facing data science efforts: design and develop algorithms and models, build and monitor operational data pipelines, leverage SQL/NoSQL and cloud architectures, query and migrate data via APIs, program in Python/JavaScript/Java, guide teammates, and translate complex data into actionable insights for decision-making.

Entry-level Data Scientist to develop, train, and deploy statistical and machine learning models (regression, SVM, neural nets) on large datasets using R/Python/Spark. Tasks include data access and quality improvements, anomaly detection, model building, documentation, and collaborating with cross-functional teams to deliver analytic products, particularly for health insurance use cases.

This role involves developing and implementing statistical models, leading data science techniques, applying machine learning to business challenges, and communicating insights to stakeholders.

The Data Scientist will design predictive models, analyze immigration data, create dashboards, and communicate technical findings to agency leadership.

The intern will assist the data science team by working on projects related to Ardian's portfolio assets and company-wide initiatives, requiring autonomy with supervision.

The Junior Data Scientist supports a federal program by collecting, cleaning, validating, and analyzing performance data, building scripts, and developing visual dashboards.