Remote Data Science Director Jobs
Remote Data Science Director jobs are open across the U.S. at remote-first firms and distributed teams in sectors from technology and fintech to healthcare and e-commerce. Employers hiring remotely right now include CVS Health, ZS Associates, and eBay. Scan the live roles below and apply to whichever ones fit.
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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.
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Find JobsRemote Data Science Director 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 director jobs.
- 7 to 10 years of experience in data science with at least 3 in a people management role
- Proficiency in Python, SQL, and machine learning frameworks such as scikit-learn or PyTorch
- Experience building and deploying production-grade ML models in cloud environments like AWS, GCP, or Azure
- Bachelor's or master's degree in statistics, computer science, mathematics, or a related quantitative field
- Demonstrated ability to translate business problems into data science roadmaps and communicate findings to executives
- Familiarity with MLOps practices, model monitoring, and data pipeline tools such as Airflow or Databricks
Tips for Your Remote Data Science Director Job Search
Apply early to remote roles that fit
Migrate Mate lists remote data science director openings from across the U.S. in one place, so you can find roles that match your background and apply directly without sorting through mixed location listings.
Show async leadership in your portfolio
Remote employers need evidence you can lead without in-person context. Include writing samples, strategy memos, or documented frameworks that show how you've aligned distributed teams and communicated data roadmaps through written channels rather than meetings.
Target remote-first companies deliberately
Remote-first firms and distributed teams have built their data functions around location-independent leadership from the start. Prioritize these over companies that added remote as an option, because their processes, tooling, and culture are designed around the way you'll actually work.
Prepare for remote-specific interview questions
Remote data science director interviews consistently probe how you've managed distributed teams, resolved ambiguity without in-person cues, and kept stakeholders aligned across time zones. Prepare specific examples using tools like Slack, Notion, Confluence, or Looker in a fully async context.
Remote Data Science Director Jobs: Frequently Asked Questions
How do I get a remote data science director job?
Target remote-first companies and distributed teams that run data functions without a central office, because they're built for remote leadership from day one. Remote employers screen hard for self-direction, clear async written communication, and the ability to align cross-functional stakeholders without in-person context. Demonstrating that you've led distributed data teams, shipped measurable results independently, and communicated strategy through written documents gives you a concrete edge over candidates with only office-based experience.
Which companies hire remote data science directors?
Companies hiring remote data science directors right now include CVS Health, ZS Associates, and eBay, based on current remote listings on Migrate Mate as of September 2026. Remote-first technology firms, distributed fintech platforms, and digital health organizations are among the most consistent sources of these openings, since their operating model depends on leaders who can run data functions across time zones.
Can you get a remote data science director job with no experience?
Yes, but remote data science director roles are harder to land without experience because remote employers need someone who can operate independently from day one without in-office oversight. Entry points include leading a data function at an early-stage remote startup, building a visible portfolio of end-to-end projects, and demonstrating written communication skills that replace the clarity normally built through in-person collaboration. Showing autonomous delivery of measurable outcomes opens the door more than credentials alone.
Do you need a degree for remote data science director jobs?
Not always. Remote employers hiring data science directors weigh demonstrated ability to lead teams, define data strategy, and deliver business impact more heavily than a specific credential. A strong portfolio of shipped projects, measurable outcomes, and evidence of cross-functional leadership can substitute for a formal degree at many remote-first companies, particularly in technology and product-led organizations where results are more visible than titles.
Which industries hire the most remote data science directors?
Remote data science director roles concentrate in Technology & Software, Insurance, and Science & Research, based on current remote listings on Migrate Mate as of September 2026. These sectors rely on distributed teams that process large volumes of data across geographies, making remote data science leadership a practical fit rather than an exception to their operating model.
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