Remote Data Science Manager Jobs
Remote Data Science Manager jobs are open across the U.S. at remote-first firms, distributed tech companies, and enterprise organizations hiring data leaders for fully distributed teams. Sectors including CVS Health, ZS Associates, and eBay are actively filling these roles right now. Scan the live roles below and apply to whichever ones fit.
Find JobsOverview
Showing 5 of 77+ Remote Data Science Manager jobs
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 Manager Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote Data Science Manager 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 manager jobs.
- 5+ years of experience in data science or machine learning with at least 2 years managing a team
- Proficiency in Python or R and familiarity with SQL for data querying and analysis
- Experience deploying machine learning models in production environments at scale
- Ability to communicate data science findings clearly to non-technical executive stakeholders
- Experience working with cloud platforms such as AWS, GCP, or Azure
- Bachelor's or master's degree in statistics, computer science, mathematics, or a related quantitative field
Tips for Your Remote Data Science Manager Job Search
Apply early to remote roles that fit
Migrate Mate lists remote data science manager openings from across the U.S. in one place. Search for roles that match your stack and team-size experience, then apply directly. Remote postings from distributed teams fill fast, so moving early matters.
Show async leadership on your resume
Remote hiring managers look for evidence you can lead data teams without in-person oversight. Quantify outcomes from distributed projects, name the async tools you used like Confluence, Jira, or Notion, and describe how you unblocked teammates across time zones.
Build a public portfolio of shipped work
Remote employers can't observe you day to day, so your GitHub, case studies, or published notebooks do the credibility work. Include end-to-end projects that show model deployment, stakeholder communication, and team coordination, not just exploratory analysis.
Prepare for the remote interview format
Distributed teams almost always interview asynchronously first, often with a take-home case or a recorded intro. Practice concise written and recorded answers that demonstrate strategic thinking without relying on whiteboard collaboration or body language to carry your points.
Remote Data Science Manager Jobs: Frequently Asked Questions
How do I get a remote data science manager job?
Target companies built around distributed teams, including remote-first SaaS firms, fintech companies, and digital health organizations, because they hire data science managers without requiring on-site presence. Remote employers screen hard for async written communication, self-directed project leadership, and the ability to unblock distributed data teams without daily standups. Demonstrating Python, SQL, and MLOps fluency alongside a portfolio of cross-functional projects gives your application a clear edge.
Which companies hire remote data science managers?
Employers currently hiring remote data science managers include CVS Health, ZS Associates, and eBay, per current remote listings on Migrate Mate as of September 2026. Remote-first technology companies, distributed financial services firms, and digital health organizations make up the largest share of these openings because their teams are built to operate across time zones.
Can you get a remote data science manager job with no experience?
Yes, but remote data science manager roles with no prior management experience are hard to land because distributed teams need someone who can operate independently from day one. Early entry paths include leading a data squad on open-source or contract projects, managing junior analysts on a freelance basis, and building a public record of shipped work. Remote-first startups are more open to first-time managers who show strong async communication and a clear technical portfolio.
Do you need a degree for remote data science manager jobs?
Not always. Remote employers weigh demonstrated leadership of data teams, a portfolio of shipped models or analytics products, and proficiency in tools like Python, SQL, and cloud data platforms heavily alongside or instead of formal credentials. A master's degree in a quantitative field is common among candidates, but employers hiring remotely often prioritize what you've built and shipped over where you studied.
Which industries hire the most remote data science managers?
Remote data science manager roles concentrate in Technology & Software, Insurance, and Science & Research, based on current remote listings on Migrate Mate as of September 2026. Those sectors hire data science managers remotely because their product and revenue decisions depend on distributed data teams delivering continuous modeling and analytics without geographic constraints.
See All 77 Remote Data Science Manager Jobs
Find roles that match your experience and apply in just a few clicks.
Find Jobs