Remote Data Science Lead Jobs
Remote Data Science Lead jobs are in active demand across the U.S., with remote-first firms and distributed tech, finance, and healthcare teams posting consistently. Employers hiring right now include CVS Health, ZS Associates, and eBay. See the openings below and apply to the ones that match your experience.
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Lead Data Scientist, Data Science
National Grid is hiring an Lead Data Scientist, for our Syracuse, Brooklyn, Hicksville NY or Waltham MA office. This is a Hybrid Role with work from home availability.
Job Purpose
The Customer Performance Lab is seeking a highly motivated Lead Data Scientist to lead the next generation of AI-enabled analytics solutions across the Customer Organization.
This role will focus on applying Generative AI, machine learning, semantic modeling, and enterprise data platforms to transform how business users consume insights, interact with data, and make decisions. The successful candidate will develop AI-powered analytics solutions that leverage customer operational data, call transcripts, knowledge stores, and semantic layers to deliver scalable business value.
This position will partner closely with Customer Operations, IT, and Business Transformation teams to drive AI adoption and modernize the analytics experience
Key Accountabilities
- Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions that combine AI models with enterprise knowledge stores, semantic layers, and operational data to improve response accuracy and business relevance.
- Build and maintain AI knowledge architectures, including metadata frameworks, vector stores, business glossaries, semantic models, and contextual data repositories that enable AI systems to understand Customer Operations data and processes.
- Develop reusable AI skills, agents, copilots, and prompt frameworks that automate analytical workflows, KPI interpretation, root cause analysis, dashboard generation, and insight discovery.
- Lead AI cost optimization initiatives by leveraging knowledge stores, retrieval patterns, caching strategies, model selection, and token management techniques to reduce operational expenses while maintaining performance.
- Partner with engineering teams to deploy AI capabilities into business applications, dashboards, and web-based solutions.
- Hands-on experience building and deploying RAG (Retrieval-Augmented Generation) solutions.
- Experience with vector databases, embeddings, semantic search, and document retrieval techniques.
- Experience integrating LLMs through APIs such as OpenAI, Snowflake Cortex, Databricks AI, Anthropic, or similar platforms.
- Experience with prompt engineering, grounding, hallucination mitigation, and AI evaluation frameworks.
#LI-SA1
Qualifications
- Bachelor's, Master’s, PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field.
- Strong Python development skills with demonstrated experience building production-ready analytics, AI, automation, API integration, or data engineering solutions.
- Experience working with enterprise AI technologies, including AI/LLM APIs, prompt engineering, retrieval frameworks, AI assistants, copilots, or workflow automation solutions.
- Experience with Retrieval-Augmented Generation (RAG), vector search, knowledge stores, machine learning, statistical analysis, or predictive modeling is highly desirable.
- Experience deploying solutions through APIs, web applications, dashboards, or enterprise reporting platforms is preferred.
- Strong SQL and data platform experience, including data modeling, transformation, and optimization within modern cloud environments such as Snowflake, Databricks, Microsoft Fabric, or equivalent platforms.
Salary
MA: $153,000 - $180,000 a year DNY: $164,000 - $192,000 a year UNY: $136,000 - $160,000 a year.
National Grid utilizes an assessment that evaluates the job qualifications/characteristics using AI or statistically based scoring.
This position has a career path which provides for advancement opportunities within and across bands as you develop and evolve in the position; gaining experience, expertise and acquiring and applying technical skills. Candidates will be assessed and provided offers against the minimum qualifications of this role and their individual experience.
National Grid is committed to providing equal employment opportunities to all employees and applicants for employment regardless of protected class. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, or any other protected status in accordance with applicable federal, state, and local laws. National Grid maintains affirmative action programs for individuals with disabilities and protected veterans.
Our employment practices are designed to ensure that all individuals are treated fairly and with respect throughout the hiring process and during employment. National Grid complies with all applicable federal, state, and local anti-discrimination laws. We are dedicated to fostering a workplace that is free from unlawful discrimination and harassment, and we encourage a culture of respect for all.
Lead Data Scientist, Data Science
National Grid is hiring an Lead Data Scientist, for our Syracuse, Brooklyn, Hicksville NY or Waltham MA office. This is a Hybrid Role with work from home availability.
Job Purpose
The Customer Performance Lab is seeking a highly motivated Lead Data Scientist to lead the next generation of AI-enabled analytics solutions across the Customer Organization.
This role will focus on applying Generative AI, machine learning, semantic modeling, and enterprise data platforms to transform how business users consume insights, interact with data, and make decisions. The successful candidate will develop AI-powered analytics solutions that leverage customer operational data, call transcripts, knowledge stores, and semantic layers to deliver scalable business value.
This position will partner closely with Customer Operations, IT, and Business Transformation teams to drive AI adoption and modernize the analytics experience
Key Accountabilities
- Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions that combine AI models with enterprise knowledge stores, semantic layers, and operational data to improve response accuracy and business relevance.
- Build and maintain AI knowledge architectures, including metadata frameworks, vector stores, business glossaries, semantic models, and contextual data repositories that enable AI systems to understand Customer Operations data and processes.
- Develop reusable AI skills, agents, copilots, and prompt frameworks that automate analytical workflows, KPI interpretation, root cause analysis, dashboard generation, and insight discovery.
- Lead AI cost optimization initiatives by leveraging knowledge stores, retrieval patterns, caching strategies, model selection, and token management techniques to reduce operational expenses while maintaining performance.
- Partner with engineering teams to deploy AI capabilities into business applications, dashboards, and web-based solutions.
- Hands-on experience building and deploying RAG (Retrieval-Augmented Generation) solutions.
- Experience with vector databases, embeddings, semantic search, and document retrieval techniques.
- Experience integrating LLMs through APIs such as OpenAI, Snowflake Cortex, Databricks AI, Anthropic, or similar platforms.
- Experience with prompt engineering, grounding, hallucination mitigation, and AI evaluation frameworks.
#LI-SA1
Qualifications
- Bachelor's, Master’s, PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field.
- Strong Python development skills with demonstrated experience building production-ready analytics, AI, automation, API integration, or data engineering solutions.
- Experience working with enterprise AI technologies, including AI/LLM APIs, prompt engineering, retrieval frameworks, AI assistants, copilots, or workflow automation solutions.
- Experience with Retrieval-Augmented Generation (RAG), vector search, knowledge stores, machine learning, statistical analysis, or predictive modeling is highly desirable.
- Experience deploying solutions through APIs, web applications, dashboards, or enterprise reporting platforms is preferred.
- Strong SQL and data platform experience, including data modeling, transformation, and optimization within modern cloud environments such as Snowflake, Databricks, Microsoft Fabric, or equivalent platforms.
Salary
MA: $153,000 - $180,000 a year DNY: $164,000 - $192,000 a year UNY: $136,000 - $160,000 a year.
National Grid utilizes an assessment that evaluates the job qualifications/characteristics using AI or statistically based scoring.
This position has a career path which provides for advancement opportunities within and across bands as you develop and evolve in the position; gaining experience, expertise and acquiring and applying technical skills. Candidates will be assessed and provided offers against the minimum qualifications of this role and their individual experience.
National Grid is committed to providing equal employment opportunities to all employees and applicants for employment regardless of protected class. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, or any other protected status in accordance with applicable federal, state, and local laws. National Grid maintains affirmative action programs for individuals with disabilities and protected veterans.
Our employment practices are designed to ensure that all individuals are treated fairly and with respect throughout the hiring process and during employment. National Grid complies with all applicable federal, state, and local anti-discrimination laws. We are dedicated to fostering a workplace that is free from unlawful discrimination and harassment, and we encourage a culture of respect for all.
See All 77 Remote Data Science Lead Jobs
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Find Remote Data Science Lead JobsRemote Data Science Lead Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Insurance
- Science & Research
- Consulting & Professional Services
- Energy
What Employers Look For
The qualifications that appear most often in remote data science lead jobs.
- 5+ years of experience in data science with at least 2 years in a lead or senior role
- Proficiency in Python or R along with SQL for data manipulation and modeling workflows
- Experience deploying machine learning models to production environments at scale
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for data infrastructure
- Demonstrated ability to mentor junior data scientists and manage cross-functional projects
- Graduate degree in statistics, computer science, mathematics, or a closely related field
Tips for Your Remote Data Science Lead Job Search
Build an async-ready work sample
Remote employers evaluate whether you can lead and communicate without real-time check-ins. Package a past project as a written case study, including your decision-making process, the tools you used, and the outcome. This replaces the whiteboard interview and signals distributed-team readiness.
Target remote-first companies specifically
Remote-first firms have built their entire data workflow around distributed collaboration, so you'll join a team with established async practices rather than retrofitting office norms. Prioritize companies whose engineering and data teams are explicitly remote-first when reviewing openings.
Apply early to remote roles that fit
Migrate Mate lists remote data science lead openings from across the U.S. in one place, so you can find roles that match your stack and seniority level and apply directly. Applying in the first few days of a posting gives you a real advantage before the pipeline fills.
Sharpen your written technical communication
Remote data science leads present findings, align stakeholders, and document decisions almost entirely in writing. Practice writing crisp model summaries and recommendation memos. Employers will notice if you communicate ambiguity, tradeoffs, and results clearly in writing during the interview process itself.
Remote Data Science Lead Jobs: Frequently Asked Questions
How do I get a remote data science lead job?
Remote data science lead roles go to candidates who can demonstrate both technical depth and the ability to lead distributed teams without hand-holding. Remote employers screen hard for self-direction, clear async written communication, and experience shipping models in production. Showcasing work through GitHub, case studies, or published results matters more than a polished resume alone, and familiarity with tools like dbt, Airflow, or MLflow signals readiness for distributed workflows.
Which companies hire remote data science leads?
Remote data science lead roles are posted by CVS Health, ZS Associates, and eBay and others right now, based on current remote listings on Migrate Mate as of September 2026. Remote-first technology companies, fintech scale-ups, and distributed healthcare and analytics firms make up the bulk of hiring for this role.
Can you get a remote data science lead job with no experience?
Yes, but remote data science lead roles are harder to break into without experience because remote employers expect you to work independently and guide others from day one. Early-career candidates do best targeting remote-first startups or smaller distributed teams where the scope is narrower. A strong project portfolio, open-source contributions, and demonstrated async communication skills can open doors when direct experience is thin.
Do you need a degree for remote data science lead jobs?
Not always. Many remote employers weigh demonstrated skills, portfolio work, and shipped projects alongside or instead of a formal degree for data science leads. What matters most is your ability to lead a remote data function, translate business problems into models, and communicate results clearly to stakeholders across time zones. A degree helps, but a strong record of real work and outcomes carries significant weight.
Which industries hire the most remote data science leads?
Most remote data science lead openings sit in Technology & Software, Insurance, and Science & Research, per current remote listings on Migrate Mate as of September 2026. These sectors favor distributed team structures that make hiring remote data science leads a practical default rather than an exception.
See All 77 Remote Data Science Lead Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Data Science Lead Jobs