Top Remote Entry Level Data Science Jobs in Boston, MA

Remote Danish language annotator to review and label text and images, draw bounding boxes, answer structured questions, and write short summaries following annotation guidelines. No prior experience required; on-the-job training provided. 30–40 hours/week, $8/hour, minimum 6-month commitment.

Review and annotate Chinese text and images to train AI: draw bounding boxes, answer structured questions, write short summaries, and follow annotation guidelines. Remote, long-term contract (minimum 6 months), 30–40 hours/week, paid hourly with a short language assessment required.

Lead clinical data science initiatives supporting clinical trial analysis and strategic decision-making. Responsibilities include designing data science strategies, identifying analytical requirements, overseeing statistical models and tools, mentoring team members, and communicating insights to stakeholders. The role requires clinical research data analysis experience, statistical software expertise, data visualization skills, leadership, collaboration, and approximately 15% travel.

Partner with AI labs to improve frontier models by designing targeted data collection workflows, analyzing experimental results, and implementing quality controls. The role involves evaluating model behavior, reducing bias, supporting model safety and alignment, and translating technical findings into actionable insights for AI researchers and customers. Python is used for data analysis, pipeline development, and workflow prototyping.

Leads data science and reporting initiatives for a commercial insurance organization, including master data management, dashboard and scorecard development, reporting-environment design, data warehouse support, data integrity, normalization, data cleansing, troubleshooting, and end-user training.

Own Alpaca’s growth data strategy across acquisition, activation, retention, referral, and monetization. Build experimentation frameworks, causal and incrementality analyses, funnel and cohort models, LTV/CAC and churn forecasts, marketing measurement, governed growth metrics, and self-serve analytics. Partner with Product, Marketing, Sales, Engineering, and Finance to influence strategy and roadmaps, communicate insights to leadership, mentor data professionals, and establish standards for growth analytics.

Prototype and validate analytical methods and LLM applications for political, media, and advertising data. Build proof-of-concept tools, datasets, pipelines, and applications, then engineer validated methods toward production. Apply statistical and data science techniques, maintain rigorous software development practices, communicate findings clearly, and collaborate with technical and non-technical stakeholders.

Analyze large datasets, identify meaningful patterns, develop machine learning models, and deliver actionable insights for business decisions. Collaborate with cross-functional teams to understand data needs, communicate findings clearly to stakeholders, and stay current with advances in data science and AI technologies.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Assist senior data scientists with data collection, preprocessing, cleaning, and basic statistical analysis. Support model development, perform basic visualizations, and document processes and findings while learning and applying data science techniques.

Own end-to-end data science for emerging content surfaces, including product experimentation, causal inference, exploratory analysis, metrics, dashboards, and strategic insights. Identify opportunities to grow content supply, creators, and engagement while improving discovery. Lead content data architecture and quality initiatives, develop source-of-truth assets, and apply advanced statistical methods such as quasi-experiments and network testing. Partner with Product, Engineering, Design, and Research to influence product direction and communicate findings to diverse audiences.