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Head Data Science Jobs (NOW HIRING)

Novartis

Associate Director, Data Science

Cambridge, MA · Hybrid

$160K - $297K/yr

This role reports to the Head of Data Science in the PKS M&S team within Translational Medicine in Biomedical Research. Key responsibilities: * Shape and advance AI-driven MIDD by integrating ...

DW Simpson

Head of Data Science - Hybrid

Fort Lee, NJ · Hybrid

$200K/yr

The ideal candidate would have 8+ years of data science marketing experience, strong leadership skills, and proficiency with SQL, Python, and Databricks. Must be comfortable reporting to the C-suite ...

Chubb

SVP, PRS - Data Science

Jersey City, NJ · On-site

$249K - $333K/yr

Responsibilities As part of the North America Data & Analytics leadership team and Head of Data Science for PRS, working collaboratively with business unit leaders to achieve ambitious business plans ...

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Citigroup, Inc.

SVP Marketing Data Science

New York, NY · On-site

The SVP, Marketing Data Science is a highly experienced and senior role, and part of the larger Media Sciences team in the Client Org, reporting to the Head of Media Science. This role will primarily ...

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All JobsHead Data Science Jobs

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 Jul 21, 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.

How to become head of data science?

To become a head of data science, professionals typically need extensive experience in data analysis, machine learning, and leadership roles, often requiring 8-10 years in data-related positions. A strong educational background in computer science, statistics, or related fields, along with skills in programming, data management, and strategic planning, is essential. Advanced degrees and certifications in data science or analytics can also enhance prospects for leadership positions.

Is 40 too late for data science?

The Head Data Science role and similar data science positions do not have strict age limits; many professionals transition into data science later in their careers. Success depends on relevant skills, experience, and continuous learning in areas like programming, statistics, and machine learning, regardless of age.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Chief Data Officer, Director of Data Science, or Lead Data Scientist, with salaries exceeding $150,000 annually and sometimes reaching over $200,000 for those with extensive experience, advanced skills in machine learning, and industry expertise. These roles typically require strong leadership, strategic thinking, and proficiency with tools like Python, R, and cloud platforms.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

What does a Head of 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 some common challenges faced by a Head of 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 are the key skills and qualifications needed to thrive as a Head of Data Science, and why are they important?

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 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.

What cities are hiring for Head Data Science jobs? Cities with the most Head Data Science job openings:
What are the most commonly searched types of Data Science jobs? The most popular types of Data Science jobs are:
What states have the most Head Data Science jobs? States with the most job openings for Head Data Science jobs include:
Head Data Science jobs near you
Infographic showing various Head Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Head of Data Science & Digital Health Innovation

Payfuture Technologies

Cambridge, MA • On-site

$196K - $342K/yr

Other

Retirement, PTO

Posted 6 days ago

Job description

Job Overview

Johnson & Johnson Innovative Medicine is recruiting for a Sr Director, Head of Data Science & Digital Health – Therapeutics Discovery. This position has a primary location of Spring House, PA and is also open to Cambridge, MA. Up to ~25% domestic/international travel may be required.

Responsibilities
  • Develop and execute a comprehensive data strategy for TD, focusing on advanced automation, data integration, and FAIR data practices; in close alignment with TD and IT.
  • Lead the design and implementation of scalable data pipelines to support discovery workflows.
  • Partner with TD leaders to build strong external partnerships with industry consortia and academic partners pertaining to Data Science needs for TD.
  • Co‑Champion data governance, analytics, model lifecycle management (MLOps), and Responsible AI standards into reusable capabilities that can be shared elsewhere in the organization.
  • Lead a core team of data scientists and engineers to support TD in reaching its strategic goals.
  • Collaborate with TD teams (such as In Silico Discovery and Discovery Technologies & Molecular Pharmacology), IT, R&D Data Science, and external partners to jointly introduce emerging technologies such as generative and agentic AI, multimodal analytics, and advanced automation tools that benefit TD’s business objectives.
  • Collaborate with TD teams (such as In Silico Discovery and Discovery Technologies & Molecular Pharmacology), IT, R&D Data Science, and external partners to jointly introduce data and technology innovation standards.
  • Work with peers across Discovery, Product Development & Supply (DPDS) and our Therapeutic Areas to generate and analyze data for opportunities in Therapeutic Discovery (e.g., experiment design, molecule design, lab process automation).
Qualifications
  • PhD or equivalent experience in Computational Biology, Chemistry, AI/ML, Applied Math/Statistics or related field.
  • 12+ years in data science for drug discovery, with experience leading teams in a matrix setting.
  • Proven expertise in creating high impact R&D innovations through data science, data engineering, and automation within scientific domains.
  • Strong experience leading the application/creation of ML/AI methods while demonstrating a deep understanding of drug discovery workflows.
  • Demonstrated success in delivering interoperable data products and scalable analytics platforms.
  • Excellent communication and matrix leadership across scientific, technical, and business stakeholders in a global organization.
Leadership Attributes
  • Strategic Vision: Ability to anticipate future trends in data science and drug discovery and translate them into actionable strategies.
  • Collaborative Influence: Skilled at building consensus and driving alignment across diverse scientific and technical teams.
  • Innovation Mindset: Passion for leveraging emerging technologies to solve complex scientific challenges.
  • Talent Development: Commitment to mentoring and growing a high‑performing team of data scientists and engineers.
  • Communication Excellence: Ability to articulate complex technical concepts to non‑technical stakeholders and executive leadership.
Equal Opportunity Employer

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected under federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act. We are committed to providing an inclusive interview process for applicants with disabilities.

Pay and Benefits

The anticipated base pay range for this position is $196,000.00 – $342,700.00. Employees may also be eligible to participate in the Company’s consolidated retirement plan (pension and 401(k)), long‑term incentive program, and a range of time‑off benefits.

Subject to the terms of their respective policies, full benefits may include: Vacation – 120 hours per calendar year; Sick time – 40 hours per calendar year (48 hours in Colorado, 56 hours in Washington); Holiday pay – 13 days per calendar year; Work, Personal and Family Time – up to 40 hours per calendar year; Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child; Bereavement Leave – 240 hours for an immediate family member; Caregiver Leave – 80 hours in a 52‑week rolling period; Volunteer Leave – 32 hours per calendar year; Military Spouse Time‑Off – 80 hours per calendar year.

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