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Head Data Science Jobs (NOW HIRING)

... head count, and regulatory requirements * Conduct an analytics initiative from ideation through ... Communicate data science outputs and support the creation of models and solutions that provide ...

... head count, and regulatory requirements * Conduct an analytics initiative from ideation through ... Communicate data science outputs and support the creation of models and solutions that provide ...

... head count, and regulatory requirements * Conduct an analytics initiative from ideation through ... Communicate data science outputs and support the creation of models and solutions that provide ...

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... head count, and regulatory requirements * Conduct an analytics initiative from ideation through ... Communicate data science outputs and support the creation of models and solutions that provide ...

... head count, and regulatory requirements * Conduct an analytics initiative from ideation through ... Communicate data science outputs and support the creation of models and solutions that provide ...

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Head Data Science information

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$37.5K

$122.7K

$196.5K

How much do head data science jobs pay per year?

As of Sep 14, 2026, the average yearly pay for head data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What does a head data science do?

A Head of Data Science is responsible for leading and managing the data science team within an organization. They oversee the development and implementation of data-driven strategies, ensuring that the team delivers valuable insights and predictive models to support business goals. This role involves collaborating with other departments, setting the vision for data initiatives, and ensuring best practices in data analysis and machine learning are followed. Additionally, the Head of Data Science often mentors team members and helps shape the organization's overall data strategy.

What are the key skills and qualifications needed to thrive as a head data science?

To thrive as a Head of Data Science, you need advanced expertise in statistics, machine learning, data modeling, and a strong background in computer science or a related quantitative field, often supported by a master's or Ph.D. Proficiency with programming languages like Python or R, big data platforms such as Hadoop or Spark, and familiarity with cloud-based analytics tools are typically required. Strategic leadership, excellent communication skills, and the ability to mentor and inspire teams are crucial soft skills for this role. These abilities are essential to drive data-driven decision-making, foster innovation, and align analytics initiatives with organizational goals.

What are some common challenges faced by a head data science when building and leading a data science team?

As a Head of Data Science, one of the main challenges is balancing strategic leadership with hands-on technical guidance. You'll often need to align the team's goals with broader business objectives while ensuring that team members have the right mix of skills and resources. Additionally, fostering effective collaboration between data scientists, engineers, and business stakeholders can be complex, especially in cross-functional environments. Managing expectations around project timelines and communicating technical insights in a clear, actionable way are also key aspects of the role.

What is the difference between Head Data Science vs Data Science Manager?

AspectHead Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, setting data science vision, overseeing multiple teamsTeam management, project delivery, coordinating data science projects
Required SkillsAdvanced analytics, leadership, strategic planningTeam management, technical expertise, project management
ExperienceSenior data science background, leadership rolesData science experience with managerial responsibilities
Work EnvironmentExecutive level, cross-departmental collaborationTeam-focused, project-oriented

The Head Data Science typically holds a strategic, leadership role overseeing the entire data science function, while the Data Science Manager focuses on managing teams and project execution. Both roles require strong technical backgrounds, but the Head Data Science emphasizes vision and strategy, whereas the Data Science Manager concentrates on operational management.

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What cities are hiring for Head Data Science jobs?

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What are the most commonly searched types of Data Science jobs?

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What states have the most Head Data Science jobs?

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What are popular job titles related to Head Data Science jobs?

For Head Data Science jobs, the most frequently searched job titles are:

Infographic showing various Head Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Science & AI Delivery Lead

New York, NY

Full-time

Medical, Retirement, PTO

Re-posted 16 days ago


Key responsibilities

  • Own the operational running of AI delivery workstreams, ensuring timely and focused project execution.

  • Provide technical guidance on solution design, model selection, and architecture decisions, and review technical outputs to maintain quality standards.

  • Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services.


Job description

This is your opportunity to join AXIS Capital - a trusted global provider of specialty lines insurance and reinsurance.  We stand apart for our outstanding client service, intelligent risk taking and superior risk adjusted returns for our shareholders. We also proudly maintain an entrepreneurial, disciplined and ethical corporate culture.  As a member of AXIS, you join a team that is among the best in the industry.

At AXIS, we believe that we are only as strong as our people. We strive to create an inclusive and welcoming culture where employees of all backgrounds and from all walks of life feel comfortable and empowered to be themselves. This means that we bring our whole selves to work.

All qualified applicants will receive consideration for employment without regard to any protected characteristic, including age, color, disability, ethnicity, gender identity, marital status, national origin, pregnancy, race, religion, sex, sexual orientation, veteran status, or any basis prohibited by the laws that govern its operations.

How does this role contribute to our collective success?

Data and analytics are of critical importance for AXIS. Simply put, we want to turn data into information, that can be used to:

  • Enable decisions to be made with confidence, based on information not just intuition.

  • Be more proactive, using information to identify new opportunities, and getting to them before our competitors.

  • Realize cost savings, finding ways to make processes more efficient, enabling our people to focus on using their skills to further add business value.

This team is working to transform the way in which we do business and to enable us to effectively leverage the latest AI advancements to our competitive advantage. The Data Science & AI Delivery Lead is a key leadership role within this team, acting as the deputy to the Head of Data Science & AI Delivery and ensuring the smooth day-to-day running of AI delivery operations.

The Data Science & AI Delivery Lead is the technical delivery leader for AI, machine learning, and advanced analytics solutions. This role owns technical execution, engineering standards, solution architecture, deployment quality, and production delivery of AI capabilities. This role focuses on how solutions are designed, built, deployed, and scaled.


What will you do in this role?

The Data Science & AI Delivery Lead acts as the right hand to the Head of Data Science & AI Delivery, taking ownership of the day-to-day execution and coordination of data science and AI delivery across strategic projects and standalone use cases. You will play a hands-on leadership role - driving technical delivery, managing workstreams, and stepping in for the Head of when required.

This is not a purely managerial role. You will be expected to work directly in the codebase, review and shape technical designs, and maintain deep fluency with the tools and techniques the team uses daily. Working closely with the Head of, you will ensure projects are delivered to a high standard, on time, and with strong stakeholder engagement.

In this role you will be responsible for:

  • Day-to-Day Delivery Leadership: Own the operational running of AI delivery workstreams, ensuring the team is focused, unblocked, and delivering against priorities. Act as the primary point of escalation when the Head of is unavailable. Own technical execution across all AI delivery workstreams. Lead architectural decisions, technical design reviews, implementation approaches, and production readiness reviews. Establish engineering standards, patterns, reusable frameworks, and delivery best practices.

  • Project Management: Own technical delivery accountability from concept through production. Ensure solutions meet security, governance, scalability, explainability, and operational support standards.

  • Technical Oversight & Contribution: Provide technical guidance on solution design, model selection, and architecture decisions, ensuring the team is taking the right approach for each use case.

  • Review code and technical outputs to maintain quality standards and contribute hands-on to Python-based development when needed, particularly during critical delivery phases or proof-of-concept work.

  • Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search).

  • Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions for performance and drift.

  • Champion engineering best practices across the team, including code review standards, documentation, version control (Git), and a clear separation between experimentation and production-ready code.

  • Technical Strategy & Architecture: Own AI solution architecture and technical design standards. Define engineering approaches for LLM applications, agentic systems, machine learning solutions, and AI platforms. Lead evaluation of emerging AI technologies and determine appropriate adoption. Establish standards for MLOps, AI observability, model lifecycle management, and responsible AI implementation.

  • Collaboration: Work closely with AXIS's Business Technology Solutions for solution architecture and delivery, and with the Program Office for planning deliveries, providing timelines, cost estimates, and status updates. Partner with Data Engineering to ensure data pipelines and lakehouse structures support AI delivery needs.

  • Team Development: Support the Head of Data Science & AI Delivery in leading and developing a growing team of Data Scientists and AI Engineers, fostering a culture of excellence, collaboration, and continuous learning. Mentor and coach team members through hands-on pairing, structured code reviews, and knowledge-sharing sessions on emerging techniques and tools. Provide hands-on coaching through architecture reviews, code reviews, pair programming, model reviews, and technical mentoring. Maintain technical credibility as a practitioner leader who remains actively involved in delivery.

  • Resource & Capacity Planning: Support the Head of in tracking the project pipeline, estimating costs (including cloud computing and API consumption), and managing resource allocation to ensure the team is effectively deployed against priorities.

  • Technology Vision: Stay current with the rapidly evolving AI landscape, including new foundation models, open-source frameworks, vector databases, orchestration tools (e.g., LangChain, Semantic Kernel), and evaluation methodologies. Bring new ideas to the team and lead proof-of-concept development to assess feasibility and value.

  • Deputising: Represent the Head of Data Science & AI Delivery in meetings, steering groups, and stakeholder forums as required, ensuring continuity of leadership and communication.

You may also be required to take on additional duties, responsibilities, and activities appropriate to the nature of this role. This role reports to the Head of Data Science & AI Delivery.
About You:

We encourage you to bring your own experience and expertise to the table so, while there are some qualifications and experiences we need you to have, we are open to discussing how your individual knowledge might lend itself to fulfilling this role and help us achieve our goals.

What you need to have:

  • Demonstrable experience delivering AI/ML solutions in a professional environment, with a track record of taking projects from concept through to production.

  • Strong technical knowledge, including expert-level Python proficiency and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow).

  • Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing.

  • Familiarity with Generative AI concepts and tooling, including working with LLMs, prompt engineering, RAG patterns, and vector search.

  • A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of deployed solutions.

  • Cloud platform experience, preferably Azure, including services such as Azure OpenAI, Azure Machine Learning, or Azure AI Search.

  • Experience managing or leading technical delivery teams while remaining hands-on, with a track record of fostering a positive, high-performing team culture.

  • Excellent communication skills and the ability to translate complex technical concepts for business stakeholders.

  • Strong project management skills, including resource estimation, progress tracking, and meeting deadlines in a fast-paced, multi-priority environment.

  • A proactive, problem-solving mindset with the ability to operate independently and step up into a leadership vacuum when needed.

What we prefer you have:

  • Experience with advanced NLP techniques beyond prompt engineering, including fine-tuning and evaluation frameworks for generative models.

  • Experience working in the (re)insurance industry, with an understanding of underwriting, claims, or actuarial data.

  • Knowledge of responsible AI practices, including bias detection, explainability, and fairness testing.


Role Factors:

In this role, you will typically be required to:

  • Attend your local office at least three (3) days per week to meet and build relationships with colleagues and the wider business.

  • Engage in company activities to grow your network and build a strong team culture.


What we offer:

For this position, we currently expect to offer a base salary in the range of $175,000 - $200,000 USD (New York, NY), $110,000 - $130,000 CAD (Halifax, Nova Scotia) Your salary offer will be based on an assessment of a variety of factors including your specific experience and work location.

In addition, you will be offered competitive target incentive compensation, with awards based on overall corporate and individual performance. On top of this, you will be eligible for a comprehensive and competitive benefits package which includes medical plans for you and your family, health and wellness programs, retirement plans, tuition reimbursement, paid vacation, and much more.

Where this role is based in the United States of America, this role is Exempt for FLSA purposes.

This posting is for an existing vacancy.