Top Software Data Science Jobs

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

The Sr. Data Scientist will utilize statistical and machine learning techniques to solve healthcare-related problems and enhance predictive modeling across products, collaborating closely with various teams.

Annotate 3D wire spans and identify visualization errors in LiDAR/camera datasets using internal tools. Maintain data integrity, document anomalies, collaborate with engineers, QA, and field techs, and deliver accurate datasets for utility infrastructure projects.

Lead and build a US-based data science capability while remaining hands-on: write code, design, deploy, and maintain production ML models on GCP (Vertex AI), mentor junior data scientists and ML engineers, establish workflows/standards and CI/CD, collaborate with US and UK data teams and product stakeholders, and implement real-time/event-driven solutions (Kafka).

Lead and grow a Data Science team for Provider Products, set analytical direction, own experimentation and measurement, review methods, partner with product and engineering, hire and develop data scientists, standardize analytics and integrate generative AI to improve workflows and outputs.

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.

Develop statistical and machine learning models using large-scale pharma datasets in Databricks, AWS, Spark, Python, and SQL. Engineer features, build ETL pipelines, validate and monitor models, and collaborate with data engineers and analysts to productionize outputs. Partner with pharma business groups to frame analytical problems and communicate insights and recommendations to technical and non-technical stakeholders.

Build and optimize machine learning models, analyze structured and unstructured data, perform feature engineering and evaluation, and identify insights for business decisions. Create dashboards and data visualizations, communicate findings to technical and non-technical stakeholders, improve data quality, and maintain data integrity and confidentiality in regulated healthcare-related environments.

Build and deploy production-grade LLM applications, AI agents, models, and scalable RAG pipelines for investment and business workflows. Architect secure MCP integrations with enterprise systems, establish MLOps and LLMOps practices, optimize model performance and latency, and develop evaluation, monitoring, governance, and rollback processes. Collaborate with data engineering and platform teams to provide secure, governed access to organizational data.

Design and operationalize ArcGIS- and Python-based geospatial data science workflows supporting CISA’s critical communications infrastructure mission. Perform spatial statistics, predictive modeling, network analysis, infrastructure mapping, and data validation. Publish web maps, scenes, and analytical services; support dashboards, briefings, training, stakeholder requests, emergency events, and classified enterprise environments. Produce formal reports and documentation while providing surge support during national security and emergency preparedness events.