This page tracks remote data scientist openings that are location-eligible for Washington.
Open jobs
2,152
Hiring companies this week
10
Salary sample
$85,000 - $178,700
Jobs added last hour
0
2152 Jobs
1224 Companies
• Coach and Develop the Team • Own the Roadmap • Build Cross-Functional Relationships • Drive Marketplace Forecasting • Own Production ML Systems • Establish Best Practices
Serving the federal government with courage, integrity, and excellence.
• Establish and maintain enterprise-level data management practices toward Level 4-5 CMMI target operating maturity. • Identify and document authoritative data sources across the OAA application and reporting portfolio. • Standardize data definitions and establish enterprise data standards and naming conventions. • Resolve duplicate and conflicting data elements across applications, databases, and reports. • Fill metadata gaps and maintain data dictionaries and report-to-data-source traceability. • Identify and remediate reporting inconsistencies across SSRS, Power BI, SharePoint, and custom applications. • Support Azure Data Engineering activities, including data pipeline and data warehouse design considerations. • Produce and maintain the Data Management Assessment and supporting data governance artifacts. • Advise developers and Government stakeholders on data quality, data lineage, and governance impacts of proposed changes. • Support ATO artifact maintenance as it relates to data handling, PII, and data classification. • Participate in recurring technical working sessions with OAA leadership and the DMC team.
A family office for your family.
• Own the Permissions & Privacy Framework – Serve as the single business owner of client data permissions and governance, defining role-based access principles and clear decision rights. Evolve the framework as appropriate • Operationalize Access & Policy Management – influence the design and manage workflows for access provisioning, deprovisioning, temporary access, advisor transitions, and confidential client handling • Govern Ongoing Permission Decisions – Act as the central project manager for complex access requests. Maintain clear policy guidance for recurring scenarios. • Build Audit, Monitoring & Risk Controls – Establish audit processes, reporting, and monitoring to ensure consistency and detect inappropriate access • Drive Cross-System Alignment – Partner with Product and Technology teams to standardize permissions across all platforms and products • Enable the Organization – Partner to create training, guidance, and FAQs to ensure employees understand access policies and processes.
• Understand sponsor data needs and be able to translate these requirements into necessary analytics • Proactively specify algorithms, models, analyses, and output required to meet sponsor needs • Draft business requirement documents and specifications. • Anticipate reporting and analytic needs to support sponsors • Understand CDISC standards and clinical trial submission processes and be able to produce data transfers and trial documentations to these standard independently • Confidence to present results and interpretations independently to sponsors • Ability to explain complex data concepts in an easily understandable way • Skilled at summarizing data in succinct, effective presentations and executive summaries. • Independently manage numerous data analytic projects and deliverables concurrently • Build, develop, and deploy data analytics, data models, reporting systems, data automation systems, dashboards and performance metrics. • Maintain reporting systems and dashboards. • Support the creation of data visualization tools. • Draft and implement Statistical Analysis Plans. • Monitoring of study data • Data transformation, transposition, cleaning, curation and reprocessing in support of data transfers and delivery to sponsors. • Implementation of CDISC data standards including SDTM and ADaM datasets. • Interact with sponsors to resolve scientific queries and participate in study planning. • Write clinical study reports, analytic reports, and other scientific reports. • Contribute to data curation and aggregation. Provide requirements and documentation of data structure and needs to support data analytics. • Analyze and report on cognitive outcome measures and cognitive tests. • Develop and QC statistical and programming output while maintaining rigorous quality standards. • Interact with project management, statistics, data management, statistical programming, and site services teams internally to support scientific analysis and reporting and support data related questions. • Develop solutions to unique customer requests relating to topics such as stratification, inclusion, reliable change monitoring, data monitoring, normative data, and other cognitive testing applications. • Generate clinical study report summary tables, data listings, figures, and other output as specified in the statistical analysis plan or other scientific reporting specification. • Review and monitor cognitive data rater performance, data monitoring findings, custom programming/statistical analysis, normative data, z-scores and computations. • Analyze and interpret cognitive data from clinical trials and research studies. • Critically evaluate internal processes and scientific methodologies. • Contribute to the development of processes, technology, and infrastructure which support the functions of scientific services and related operations. • When acting as a QC programmer, work independently from source data and ensure a 100% match of all output. • Maintain an intimate knowledge of Cogstate’s data systems. • Provide requirements for development and commercialization of new technology.
Role Description We are seeking a highly skilled Senior Data Scientist to join a fast-paced SaaS organization on a contract basis. This role is ideal for a hands-on data science professional with deep expertise in machine learning, Snowflake Cortex ML, Python, advanced SQL, and MLOps automation. The successful candidate will partner closely with business stakeholders to develop, optimize, and deploy production-grade machine learning solutions that drive business value. This is a 3 to 6-month contract with potential for permanent conversion, targeting a start date of August 1. Key Responsibilities - Machine Learning & Data Science - Design, develop, and enhance production-grade machine learning and predictive analytics models to solve complex SaaS business problems. - Maintain, optimize, and evaluate existing ML models to ensure continuous improvements in accuracy, performance, and scalability. - Apply statistical modeling and advanced machine learning techniques to extract actionable business insights from enterprise data. - Snowflake Cortex ML Development - Develop, deploy, and scale machine learning solutions natively using Snowflake Cortex ML and its broader AI capabilities. - Optimize model execution, feature engineering, and data processing architectures directly within the Snowflake ecosystem. - Collaborate with data engineering and platform teams to seamlessly integrate Cortex ML and Snowpark workflows into production systems. - MLOps & Pipeline Automation - Build, automate, and maintain robust end-to-end machine learning pipelines for model training, validation, and deployment. - Implement and govern MLOps workflows to support automated model monitoring, versioning, retraining, and continuous integration/continuous delivery (CI/CD). - Improve the reliability, automation, and scalability of production machine learning environments using Jupyter Notebooks and orchestration tools. - Data Integration & Stakeholder Collaboration - Perform complex SQL-based data extraction, transformation, feature engineering, and integration of third-party data sources. - Partner directly with cross-functional stakeholders in Product, Engineering, and Business teams to translate operational requirements into technical AI solutions. - Document workflows and present clear technical findings, methodologies, and strategic recommendations to both technical and non-technical audiences. Qualifications - 7 or more years of professional experience in Data Science or Machine Learning. - Demonstrated experience developing, optimizing, and supporting production-grade machine learning and predictive models. - Strong industry experience within a Software-as-a-Service (SaaS) or modern digital product environment. - Hands-on experience building and deploying machine learning solutions utilizing Snowflake Cortex ML. - Expert-level programming skills in Python and advanced SQL querying. - Proven experience establishing and automating MLOps pipelines, including model deployment, monitoring, versioning, and CI/CD. - Strong background in data integration, data quality verification, and advanced feature engineering. - Experience collaborating directly with business stakeholders to translate business needs into technical AI and ML solutions. Preferred Qualifications - Hands-on experience with Large Language Models (LLMs) or Generative AI integrations. - Experience utilizing Snowpark and modern Snowflake AI/ML platform capabilities. - Practical familiarity with Git, version control systems, and enterprise data pipelines. - Experience using cloud-based AI platforms and advanced production analytics tools. Core Skills & Attributes - Exceptional analytical, problem-solving, and statistical modeling capabilities. - Strong communication and presentation skills, with the ability to translate technical AI concepts into clear business value. - Excellent stakeholder management and collaboration skills across cross-functional engineering, product, and business domains. - Self-motivated with a strong attention to detail and the ability to operate independently in a fully remote environment. Benefits - Competitive salary - Remote location - Senior Level (7 or more years of experience)
Tiger Analytics is a fast-growing advanced analytics consulting firm, recognized as a trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data.
Role Description Tiger Analytics is looking for a Senior Data Scientist with a good blend of data analytics background, practical experience in Operation research strategies and Pricing Analytics within supply chains, and strong coding capabilities to add to our team. - Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming. - Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG. - Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization. - Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain. - Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. - Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies. - Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement. - Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization. - Collaborate, coach, and learn with a growing team of experienced Data Scientists. Qualifications - Proven experience 6+ years working as a Data Scientist, with a focus on supply chain optimization and inventory allocation. - MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field. - Experience with using mathematical programming solvers such as Gurobi, Xpress MP, CPLEX, or Google OR Tools in applications. - Experience with MLflow and model lifecycle management. - Experience building end-to-end ML pipelines in production. - Solid understanding of statistical methods, optimization techniques, and predictive modelling concepts. - Strong proficiency in programming languages such as Python, Pyspark and SQL, and experience working with data analysis and machine learning libraries. - Ability to apply various analytical models to business use cases. - Exceptional communication and collaboration skills to understand business partner needs and deliver solutions and explain to business stakeholders. Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Company Description Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce. - Market leaders in AI and analytics consulting in the CPG & retail industry. - Over 40% of revenues coming from the CPG & retail sector. - Fastest-growing sector with a focus on beefing up talent.
Molina Healthcare is a Fortune 500 managed care company with a storied history that dates back to 1980 and the opening of a medical clinic by Dr. C. David Molina. As an employer, M
Role Description We are seeking a highly skilled GenAI / Agentic AI Engineer to design, build, and deploy autonomous, LLM-powered systems that solve complex business problems at scale. This role focuses on agentic workflows, retrieval-augmented generation (RAG), tool orchestration, evaluation, and production deployment of GenAI systems. You will work at the intersection of LLMs, systems engineering, and applied ML, building intelligent agents that reason, plan, interact with tools, and operate reliably in real-world environments—particularly across regulated domains such as healthcare. Job Duties - Agentic AI & GenAI System Development: - Design, build, and deploy agentic AI systems using LLMs, tools, memory, and planning frameworks. - Implement multi-agent and single-agent workflows for autonomous task execution, decision support, and orchestration. - Develop tool-using agents (function calling, structured outputs, APIs, databases, workflows). - Retrieval-Augmented Generation (RAG): - Design and optimize RAG pipelines, including document ingestion, chunking strategies, embeddings, vector stores, and retrieval ranking. - Implement advanced retrieval techniques (hybrid search, metadata filtering, re-ranking, query rewriting). - Evaluate and tune RAG systems for accuracy, latency, grounding, and hallucination reduction. - Model Adaptation & Optimization: - Fine-tune and adapt foundation models (instruction tuning, LoRA, adapters) for domain-specific use cases. - Optimize prompts, schemas, and system instructions for reliability and determinism. - Apply reinforcement or feedback-driven optimization where applicable (human or automated eval loops). - Evaluation, Monitoring & Governance: - Define evaluation frameworks for GenAI systems, including task success, factuality, grounding, latency, and cost. - Build monitoring and observability for agent behavior, tool calls, and failure modes. - Partner with governance and risk teams to ensure responsible AI practices, traceability, and compliance. - Production Deployment & MLOps for GenAI: - Deploy GenAI and agentic systems into production using cloud-native architectures. - Implement CI/CD, versioning, rollback, and runtime safeguards for LLM applications. - Optimize systems for performance, cost efficiency, and scalability. - Collaboration & Leadership: - Collaborate closely with software engineers, product managers, data scientists, and business stakeholders. - Translate ambiguous business problems into well-structured agentic solutions. - Mentor junior engineers and contribute to GenAI best practices and internal standards. Qualifications - Strong Python proficiency and experience building production-grade services. - Deep understanding of LLMs and foundation models (GPT, Claude, Llama, etc.). - Hands-on experience with agent frameworks (e.g., LangGraph, Semantic Kernel, DSPy, AutoGen, CrewAI, custom frameworks). - Strong knowledge of RAG architectures, vector databases, and embedding models. - Experience with structured outputs, function calling, JSON schemas, and tool orchestration. - Familiarity with LLM evaluation techniques and failure mode analysis. - Experience with APIs, microservices, and distributed systems. Requirements - Master’s Degree in Computer Science, Data Science, Statistics, or a related field. - 6+ years’ work experience as a data scientist preferably in healthcare environment but candidates with suitable experience in other industries will be considered. - Knowledge of big data technologies (e.g., Hadoop, Spark). - Familiar with relational database concepts, and SDLC concepts. - Demonstrate critical thinking and the ability to bring order to unstructured problems. - Technical Proficiency: Strong programming skills in languages such as Python and R, and experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. - Statistical Analysis: Excellent understanding of statistical methods and machine learning algorithms, including k-NN, Naive Bayes, SVM, and neural networks. - Experience with Agentic Workflows: Familiarity with designing and implementing agentic workflows that leverage AI agents for autonomous operations. - RAG Techniques: Knowledge of retrieval-augmented generation techniques and their application in enhancing AI model outputs. - Model Fine-Tuning Expertise: Proven experience in fine-tuning models for specific tasks, ensuring they meet the required performance metrics. - Data Visualization: Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex data insights effectively. - Database Management: Experience with SQL and NoSQL databases, data warehousing, and ETL processes. - Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on developing innovative solutions to complex challenges. Preferred Education - PHD or additional experience. Preferred Experience - Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio etc.) for working with AI workflows and deploying models. - Familiarity with natural language processing (NLP) and computer vision techniques. Benefits Molina Healthcare offers a competitive benefits and compensation package. Molina Healthcare is an Equal Opportunity Employer (EOE) M/F/D/V.
Rare mission. Fearless team. Incredible possibilities.
• Management of data management vendors providing consistent team direction/guidance and monitoring quality of work through vendor audits and key performance metrics. • Development and maintenance of program level DM deliverable timelines in accordance with program development strategy. Actively drives internal and external timeline negotiations, as needed. • Represent data management at cross-functional team meetings providing accurate study status updates and proactive communication/escalation of data management issues and risks. • Facilitate cross-functional sponsor review meetings of eCRF design and edit check specifications. • Facilitate and perform cross-functional sponsor EDC user acceptance testing. • Facilitate the development of data transfer agreements with central/specialty labs and other external data vendors. Ensuring data quality from data capture to reporting. • Facilitate the development and implementation of key data and metrics reports/listings. • Perform sponsor review of DM essential documents including annotated CRFs, eCRF Completion Guidelines, Data Management Plans and DB Go Live and Lock documentation.
• Provides technical expertise across all aspects of Data Management • Serves as the primary Data Management point of contact for assigned studies • Ensures contracted Data Management deliverables are met with a focus on quality and timeliness • Manages study data delivery timelines, including Go-Live, Interim Deliveries, and Final Database Lock • Collaborates closely with cross-functional teams across global geographies • May provide mentorship to Assistant Data Managers and Data Management peers • Reviews and analyzes study metrics to identify trends and summarize study health • Reviews agreements to manage sponsor-specific metrics and performance indicators • Attends cross-functional meetings and prepares meeting minutes and action logs • Ensures compliance with Standard Operating Procedures and ICH/GCP guidelines • Identifies quality issues, ensuring appropriate resolution and closure. • Participates in internal, sponsor, and regulatory audits and inspections.
Jerry.ai is America’s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets. Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. We spend every day innovating and improving our AI-powered app to provide the best possible experience for our customers. We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. We have more than 5 million customers — and we’re just getting started. Founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing. Join our team and work with passionate, curious and egoless people who love solving real-world problems. Help us build a revolutionary product that’s disrupting a massive market.
Role Description Our Data Science & Analytics team has been a force multiplier and accelerant to our business that has helped us reach pivotal milestones in spite of headwinds and within a highly competitive market. They are a team of former McKinsey, BCG, and Bain consultants who drive data & insights, and inform decision-making across every corner of our business. - Every business unit has a Data Science team member embedded within it. - Drive our most important initiatives across product, growth, tech, and operations. - Help us go from 5M to 50M customers and become a $10B business in the next 4 years. We are hiring 4-6 people to drive impact in the following areas: - Growth Marketing - Product Development - AI & Automation - Strategic Partnerships You may see job ads for this role at different job levels. Our priority is finding the right people; we can be flexible with job title/leveling. What You'll Own - Be embedded in one of Jerry's core business areas — growth, product, AI and automation, strategic partnerships. - Define the right problems before any analysis. - Define metrics, build reports, run analyses, design experiments, and surface data insights. - Bring recommendations to your counterparts in product, growth, finance, or operations. Who You Are - First principles thinker: Break ambiguous problems into clear hypotheses. - Direct communicator: Walk skeptical stakeholders through complex findings. - Owner: Feel responsible for fixing issues, even outside your swim lane. What You'll Bring - 1+ years of experience at a consulting firm, investment bank, or high-growth technology company. - Strong analytical skills; ability to pull, structure, and interpret data independently. - Track record of owning ambiguous problems and delivering impact. - Clear, persuasive communicator who can influence decisions at the leadership level. Our Tools - SQL (Clickhouse) - Metabase - Python - Jupyter Hub - GitHub Benefits - Comprehensive benefits package including health, dental, and vision coverage. - Paid time off and paid parental leave. - 401(K) plan with employer matching. - Wellness benefits. - Equity opportunities may also be part of your total rewards package.
2,142more opportunities are still waiting for you.Log in now and take your next shot before someone else does.
Python, SQL, AI, AI/ML, Azure, PySpark
