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Head Data Science Jobs (NOW HIRING)

Rundoo

Data Science Intern

Chicago, IL · On-site

$1.20K/wk

You'll report to Rundoo's Head of Data Science, Amrit, and work with members from our go-to-market team. This role is ideal for someone who thrives on leveraging data-driven techniques and ...

Holganix

Head of Science

Kansas City, MO · On-site

As Head of Science, you will work with the executive team and company leadership to develop the ... Build and lead the teams that can establish the scientific and data moats around Holganix offerings:

Natera

OR

$114.40K - $137.40K/yr

Head of Data Engineering & Platform, Real-World Data (RWD)POSITION SUMMARY Natera is seeking a ... QUALIFICATIONS * Bachelor's, Master's or PhD degree in Computer Science, Engineering ...

Lemonade

Data Science Manager

New York, NY · On-site

$210K - $230K/yr

At Lemonade, there's no such thing as going over someone's head. We have zero tolerance for ... You'll sit within our Data Science team, owning the direction of a group of talented data ...

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How much do head data science jobs pay per year?

As of May 29, 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 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 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 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 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 May 2026, with employment types broken down into 10% As Needed, 70% Full Time, and 20% Part Time. Highlights an 77% Physical, 9% Hybrid, and 14% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Director, Data Science

Director, Data Science

Glyphic Biotechnologies

Berkeley, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Job description

About Glyphic:
At Glyphic Biotechnologies, we plan to create the protein revolution for which scientists and researchers have been waiting. We are developing a massively parallel, single-molecule proteome sequencing platform that will transform life science discovery and usher in a new era of insights into human biology and disease. To date, we have raised >$80M from venture partners and non-dilutive grant funding to achieve our vision of next generation proteome sequencing.
What we are looking for in you
We are looking for a Director-level technical leader to build and lead Glyphic's Data Science function. This is a "player-coach" role. You must be technically deep enough to guide signal-processing and ML strategy for a novel nanopore-based protein sequencing platform, while also building the team culture, processes, and infrastructure needed to later scale from a larger data organization. You will report to the VP of R&D and work closely with team leads in assay development, chemistry, and automation.
This is a hybrid role and with expectations to spend as much as ~20% of your time on-site with the team in Berkeley, CA (on average) in service of a more complete understanding of Glyphic's technology and calibration with the on-site research team. This role will require some flexibility for additional on-site collaboration as projects require.
What you'll do
Technical Leadership
  • Set the technical direction for ML model development: amino acid classification from nanopore current signals, signal segmentation, stall detection, temporal modeling, and multi-cycle analysis.
  • Drive improvements to classification accuracy through better architectures (transformers, deep learning), training strategies, and feature engineering.
  • Own the roadmap for data infrastructure: pipeline automation, data lake architecture, metadata standards, and self-serve analytics for the broader scientific team.
  • Make strategic build-vs-buy decisions for tooling, compute, and third-party platforms.

People Management
  • Provide technical and professional management to a team of data scientists and engineers to enable end-to-end analysis pipeline
  • Create an environment where high-autonomy individual contributors thrive: clear goals, minimal process overhead, rapid feedback loops.
  • Foster a culture of rigorous, reproducible analysis and clear communication of results to non-computational audiences.

Cross-Functional Partnership
  • Translate wet-lab experimental goals into computational strategies and vice versa - surface data-driven insights that reshape assay design and instrument operation.
  • Work with assay development to design experiments that generate high-quality training data and enable systematic evaluation of new chemistries (expanders, linkers, barcodes).
  • Collaborate with the Head of Automation and hardware teams on instrument data integration and real-time analysis capabilities.
  • Represent Data Science in management discussions, communicating progress, risks, and resource needs clearly.

AI Strategy
  • Champion the adoption of AI coding and analysis tools (Claude, Claude Code, etc.) across the data team and the broader organization.
  • Evaluate how generative AI and LLMs can accelerate internal workflows: automated reporting, data exploration, code generation, and literature review.

What You Need
Required:
  • MS or PhD in a quantitative field (Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, Statistics, or related)
  • 10+ years of post-academic experience in the omics space (genomics, proteomics, or related fields).
  • 4+ years of experience managing technical teams (data scientists, ML engineers, or bioinformaticians), including hiring responsibility.
    • Ability and willingness to operate as a player-coach: setting strategy while remaining hands-on with data, code, and models.
    • Exceptional ability to identify, hire, and develop talent while establishing and enforcing standards of excellence in data science
    • Capacity to develop both individual contributors and future managers within the team.
  • Deep expertise in one of the following:
    • Primary sequencing data analysis
    • Machine learning applied to biological data
    • Pipeline infrastructure and bioinformatics tooling
  • Solid understanding of signal processing, classification, and machine learning techniques (transformers, CNNs, RNNs) and comfort applying them to sequencing or time-series data
  • Practical familiarity with AWS, Nextflow, and modern bioinformatics tooling.
  • Demonstrated ability to work at the bench-to-computation interface in collaborative research environments
  • Ability to present complex technical results to non-technical stakeholders and to translate biological questions into computational approaches.

Nice to have:
  • Direct experience with sequencing data, basecalling, read-level QC or nanopore signal-level analysis (strongly preferred).
  • Experience building data infrastructure and analytics platforms in early-stage biotech.

We're looking for a teammate that:
  • Navigates complex team dynamics, partnerships, and challenges with creativity and logic.
  • Operates with adaptability, urgency, and flexibility in evolving environments, thriving in ambiguity.
  • Drives work forward without needing to be asked, taking responsibility for outcomes rather than tasks.
  • Treats obstacles as problems to be creatively solved, not reasons something can't be done.
  • Applies sound judgment to the best available information, testing, learning, and iterating.
  • Shares early and directly when assumptions change, results are unclear, or timelines are at risk.

What you can expect from this role
Work environment:
  • Collaborative culture where your ideas and expertise are valued
  • Direct impact on product development and company direction

Professional growth:
  • Build Glyphic's first dedicated data science management function, defining team structure, standards, and culture.
  • Help define the technical standards and best practices for omics data analysis while mentoring the next generation of data scientists who will adopt and advance these approaches.
  • Work with proprietary, information-rich data at scale that few organizations possess-the opportunity to develop novel approaches and methodologies that set benchmarks for the field.

Compensation
Estimated Base Salary: $215,000 - $257,000/year
This is the pay range for this position that we reasonably expect to pay. Individual compensation is based on various factors including, experience, education, skillset, and geographic location. This range is for the SF Bay Area, California location and may be adjusted to the labor market in other geographic areas. We are open to considering compensation above this range for candidates whose background and expertise exceed our expectations for the role.
Benefits and Perks:
  • Employee Stock Option Plan
  • 100% Health Plan Coverage for Employees & Dependents (Medical, Dental, & Vision)
  • Employer Retirement Contributions to 401(k)
  • Generous Paid Time Off
  • Paid Maternity and Paternity Leave
  • Health & Wellbeing Program
  • Office Snacks and Beverages
  • Regular Team Bonding Activities

We are an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Glyphic Biotechnologies are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.

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