Top Remote Data Science Jobs

The Data Scientist II will drive insights, develop models, and analyze product experiments to inform business decisions and improve member experiences in healthcare.

Design, validate, and deploy predictive models using claims, clinical, pharmacy, and lab data to improve population health, utilization management, and care quality. Partner with clinical and business teams, evaluate model performance, scale analytical approaches, and communicate insights to technical and non-technical stakeholders.

Perform quantitative real estate and urban economic analysis, applying econometric and spatial methods to synthesize property, macroeconomic, and geospatial data. Build and maintain automated data pipelines, ensure data integrity, document dataflows, and prototype ML/AI methods. Collaborate with research, GIS, and engineering teams to produce reproducible insights and analytical products for stakeholders.

Lead data science strategy across complex customer engagements, turn ambiguous business problems into repeatable ML solutions, define modeling and evaluation standards, drive data readiness and MLOps practices, mentor teams, produce reusable IP, and represent Microsoft in executive and thought-leadership forums.

The Senior Data Scientist will lead advanced quantitative analytics, manage complex data workflows, and translate business needs into analytical strategies while collaborating with client teams to deliver actionable insights.

The Lead Data Scientist will enhance analytics through predictive modeling and data engineering, focusing on quality, feature generation, and continuous learning.

As a Pricing Data Scientist, you'll develop and validate pricing models for alternative assets, collaborate with engineers, and enhance valuation accuracy through data insights.

Lead customer-facing data science engagements: manage data acquisition/cleaning, develop and evaluate scalable models, drive modeling best practices, contribute thought leadership, write extensible code, and define solution and business strategy with cross-functional teams.

Lead data science engagements with customers to acquire, clean, analyze, and model data; develop scalable operational models and evaluation methods; coach engineers on best practices; drive solution strategy, ethics, and industry thought leadership; write extensible code and collaborate across teams to deliver cloud-based AI solutions.

Seeking a skilled Data Scientist/Machine Learning Engineer to develop machine learning models, design AI systems, and collaborate in data analytics. Responsibilities include productionizing models, data engineering, and cross-functional collaboration.

Lead customer-facing data science engagements: acquire and prepare data, evaluate and operationalize models at scale, drive modeling best practices, research industry trends, write extensible code, and define solution and customer strategy while promoting ethics and privacy.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.

Lead product and program analytics for Microsoft skilling experiences. Design funnel and learner-journey analyses, define success metrics, build measurement frameworks, run experiments and causal analyses, develop competency/skill models, partner with product and engineering on telemetry, recommend content and curriculum improvements, mentor data scientists, and ensure data privacy and telemetry quality.

Lead customer-facing data science engagements: manage data acquisition and cleaning, build and evaluate scalable models, drive model best practices and ethics, write extensible code, research industry trends, define solution strategy, and collaborate across engineering and product teams to deliver AI/cloud solutions.

Analyze large marketing datasets, build predictive models for segmentation, pricing, and demand forecasting, support targeted campaigns and retention, partner with product and marketing, apply statistical and ML methods, ensure data quality with engineering, and communicate insights to stakeholders to drive conversion and retention improvements.

This role involves analyzing EHR and insurance claims data to define clinical outcomes, developing AI models, and collaborating with technical experts for manuscript preparation.

The Data Scientist at GenLogs will build machine-learning systems, analyze large datasets, and collaborate with engineering and product teams to deliver advanced logistics intelligence solutions.

Lead end-to-end data science projects: define problems, build/test hypotheses, deliver scalable solutions for productization. Perform advanced statistical and time-series analyses, collaborate cross-functionally, and translate insights into customer value while supporting deployment and system optimization.

The Staff Data Scientist leads machine learning initiatives for personalization and optimization. Responsibilities include causal measurement, LTV model development, and technical leadership across data science teams, partnering with cross-functional teams to align strategies and impact revenue outcomes.

As a Staff Data Scientist, you'll design and optimize ML systems for claims handling automation, collaborating with product and engineering teams.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.

Seeking a Senior Data Scientist to lead predictive analytics and machine learning initiatives. Responsibilities include building ML models, data management, and mentoring junior data scientists. Must have expertise in AWS and strong statistical knowledge.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.