Top Data Science Jobs

Lead client-facing data science efforts: explore, clean, analyze structured and unstructured data; build predictive models and NLP/text-mining solutions; develop visualizations; guide teammates and deliver actionable insights to inform decisions. Requires Secret clearance and a bachelors degree.

As a Mid Data Scientist, you'll leverage data science techniques and tools to analyze data sets, create algorithms, and provide actionable insights for clients in various sectors, including health and national security.

Develop and operationalize graph-based analytics for fraud detection and investigative analysis. Build graph models, apply graph algorithms and ML to detect anomalies, support entity resolution, create visualizations and dashboards, and collaborate with investigators and stakeholders to deploy and maintain production solutions.

Apply data science and ML techniques to large structured and unstructured datasets to support DoD strategic decision-making. Perform statistical analyses, build production-quality visualizations and dashboards, lead projects from scoping to delivery, mentor junior staff, collaborate with stakeholders, and communicate insights to senior leadership using distributed computing and reproducible analytic workflows.

Work with clients to analyze structured and unstructured data, develop and deploy machine learning, NLP, and predictive models, create visualizations, and apply AI/ML frameworks to solve real-world problems.

As a Senior Data Scientist, you will analyze complex data sets, develop predictive models, and guide clients in decision-making through data visualization and insights.

As a Data Scientist, you will shape data science efforts, work with teams to understand product usage, mentor junior staff, and build data products.

Lead the development of a core ontology for security config analysis, applying data science and ML techniques while collaborating with security teams.

The Data Scientist role involves developing measurement models, writing production-quality code in Python, and collaborating with teams to optimize data pipelines and ML workflows.

Analyze complex structured and unstructured data, build and maintain data pipelines, develop predictive and prescriptive models, and apply machine learning, NLP, statistical, and data engineering techniques. The role includes using cloud and distributed processing platforms, creating visualizations, communicating insights to nontechnical audiences, and delivering technical training to SOCOM personnel. Travel up to 25% is required.

Deploy machine learning solutions for enterprise Oil & Gas customers, benchmarking against existing models and delivering measurable ROI. Responsibilities include data engineering, feature engineering, validation, model optimization, data leakage prevention, and secure last-mile integrations across cloud, on-premises, and air-gapped environments. The role partners with customers, sales, research, product, and solution architecture teams while translating technical insights into business value and product roadmap priorities.

Provides technical leadership for production-scale data science and AI systems. Designs end-to-end ML platforms, autonomous and multi-agent systems, NLP, computer vision, forecasting, reinforcement learning, simulation, evaluation frameworks, and MLOps processes. Leads high-impact initiatives from problem framing through deployment, influences AI strategy, presents quantified insights to executives, establishes validation and safe-deployment standards, and mentors senior scientists and engineers.

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

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

Embedded data scientist owning analytics for a business area (growth, product, AI, or partnerships). Define problems, build metrics and analyses, run experiments, surface insights, and drive recommendations to improve key metrics and outcomes.

Embedded data scientist owning analytics end-to-end for a business unit: define problems and metrics, pull and analyze data, design experiments, build reports, surface insights, and drive recommendations that influence product, growth, and strategic decisions.

Designs and develops methods to consolidate, cleanse, integrate, and analyze structured and unstructured big data. Performs statistical and data-mining analyses using R, SAS, and MATLAB; designs data acquisition systems and databases; gathers requirements; and produces reports. Develops analytical models, algorithms, and automated processes using SQL, PHP, and Python to support manufacturing and process information products.

Designs methods to consolidate and analyze structured and unstructured big data. Performs statistical and data-mining analysis, develops analytical models and algorithms, designs data acquisition and database structures, and cleanses and integrates large datasets using SQL, PHP, and Python. Partners with internal customers on requirements and reporting while supporting manufacturing and process-information products through advanced analytics.

Develops statistical and data-mining models, automated analytical processes, and systems for consolidating large structured and unstructured datasets. Uses R, SAS, MATLAB, SQL, PHP, and Python to cleanse, integrate, and evaluate data. Partners with internal customers, product teams, service teams, and business leaders to define requirements, identify KPIs, derive insights, support manufacturing and process information products, and communicate analytical findings that improve business processes.

Develops statistical and data-mining analyses, analytical models, algorithms, and automated processes using large structured and unstructured datasets. Designs data acquisition systems, databases, and data integration methods; gathers requirements, produces reports, and supports manufacturing and process-information products. Requires collaboration with internal customers and project teams, explaining complex findings, building consensus, and occasionally leading small projects.

Embedded within a core business area, define analytics problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end with stakeholders.

Embedded data scientist working end-to-end with a business unit to define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed product, growth, AI, and partnership outcomes.

Embed on a core business team to define problems, build metrics/reports, run analyses and experiments, and drive data-informed recommendations end-to-end to improve growth, product, AI/automation, or partnerships.

Embed within a core business area to define problems, build metrics, run analyses and experiments, create reports, surface insights, and drive data-informed product, growth, AI, or partnership outcomes end-to-end.

Analyze microbiome and longitudinal clinical data, develop biomarkers and microbiome metrics using statistical and machine learning methods, and create visualizations, reports, protocols, and study reports. The role supports research, product development, scientific publications, proposals, and clinical studies while collaborating independently with microbiome experts in a remote-first startup environment.