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Director Of Data Science Jobs (NOW HIRING)

Director of Data Engineering

San Diego, CA ยท Hybrid

$170K - $230K/yr

Director of Data Engineering - San Diego, CA 3 days/week in office, 2 days/week remote, Full time M ... Works with Business Intelligence and Data Science teams to ensure data is easily accessible and ...

The Opportunity We're hiring a Director of Data to make data the indisputable engine of our results ... science, with 3+ years leading data teams - ideally at a high-growth B2B SaaS, marketplace, or data ...

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Total Wine & More is seeking a Director of Data Science to join our Technology team in our Bethesda, MD office. This role will lead multiple data science team members with a significant portfolio of ...

About the Position As the Director of Data Science at Formation Bio, you will be at the forefront of revolutionizing drug development through AI and advanced analytics. In this role, you'll lead ...

... direct or indirect team management) We recognize that exceptional candidates may follow non ... years of post-degree experience, with 4+ years in a data science or applied AI leadership role ...

VP Data Science As the VP of Data Science, you'll play a critical role in building a data-driven culture and driving strategic initiatives. You'll leverage a rich data-set built on a mature data ...

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Original Post Date: 4/3/2026 VP of Data Science Kaizen Analytix LLC, an analytics products and services company that gives clients unmatched speed to value through analytics solutions and actionable ...

We are looking for a Head of Data to lead Alpaca's ~15-person data department across Platform Engineering, Analytics Engineering, and Data Science. You will own the data strategy, the team ...

We are looking for a Head of Data to lead Alpaca's ~15-person data department across Platform Engineering, Analytics Engineering, and Data Science. You will own the data strategy, the team ...

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Director of Data Engineering We are seeking an experienced Director of Data Engineering responsible ... Bachelor's degree in Computer Science, Engineering, Data Science, or equivalent experience * 8+ ...

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Director Of Data Science information

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$54K

$154.9K

$244K

How much do director of data science jobs pay per year?

As of Jul 6, 2026, the average yearly pay for director of data science in the United States is $154,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $189,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Director of Data Science, and why are they important?

A Director of Data Science needs advanced expertise in statistical analysis, machine learning, and data strategy, typically supported by a graduate degree in a quantitative field and significant industry experience. Familiarity with big data platforms (e.g., Hadoop, Spark), programming languages (Python, R), and cloud-based analytics tools, as well as experience managing data science teams, is essential. Strong leadership, communication, and business acumen are key soft skills for aligning technical work with organizational goals and influencing stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the strategic impact of data science initiatives within the organization.

What does a director of data science do?

A director of data science oversees data science teams, develops strategies for data analysis and modeling, and ensures projects align with business goals. They often manage data infrastructure, collaborate with other departments, and require strong skills in statistics, machine learning, and leadership. The role typically involves setting priorities, managing resources, and communicating insights to stakeholders.

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 or Director of Data Science, with salaries exceeding $200,000 annually. These roles typically require extensive experience, advanced skills in machine learning and big data tools, and often involve strategic leadership responsibilities.

What are some common challenges faced by a Director of Data Science when leading cross-functional teams?

As a Director of Data Science, one of the key challenges is aligning the goals of data science teams with those of product, engineering, and business stakeholders. This often involves translating complex technical findings into actionable insights that non-technical colleagues can understand and use. Additionally, managing resource allocation and prioritizing projects across multiple departments can be demanding, especially in fast-paced environments. Building a collaborative culture and fostering open communication are crucial for overcoming these challenges and ensuring data-driven strategies deliver business value.

Is 40 too late for data science?

For a Director of Data Science, starting a career at 40 is not too late, as many professionals transition into data roles later in life. Success depends on relevant skills, experience, and continuous learning in areas like machine learning, programming, and data analysis. Age should not be a barrier if you have a strong background and stay current with industry tools and trends.

What is the 80 20 rule in data science?

The 80/20 rule, also known as Pareto principle, suggests that roughly 80% of effects come from 20% of causes. In data science, it often means that a small subset of features or data points significantly influence model performance or insights, guiding focus on the most impactful variables during analysis and feature selection.

What is the difference between Director Of Data Science vs Data Scientist?

AspectDirector Of Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's or PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic planning, team management, cross-department collaborationData analysis, model development, coding, and experimentation
Employer & Industry UsageTech companies, finance, healthcare, large enterprisesStartups, tech firms, research institutions, various industries

The main difference between a Director Of Data Science and a Data Scientist lies in their scope of responsibilities. The Director oversees strategic initiatives, manages teams, and aligns data projects with business goals, while Data Scientists focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but the Director's role emphasizes leadership and strategic planning.

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Who are the top companies hiring for Director Of Data Science jobs? The top employers for Director Of Data Science jobs are:
What states have the most Director Of Data Science jobs? States with the most job openings for Director Of Data Science jobs include:

Manager of Data Science

CLA (CliftonLarsonAllen)

Racine, WI โ€ข On-site

Full-time

Posted 16 days ago


Job description

Job Summary:
CLA (CliftonLarsonAllen) is a top 10 national professional services firm dedicated to creating opportunities for clients, people, and communities. They are seeking a Manager of Data Science to lead a team in constructing complex data solutions, overseeing AI initiatives, and ensuring high-quality delivery of analytical projects.
Responsibilities:
โ€ข Provide dayโ€‘toโ€‘day leadership, coaching, development, and performance management.
โ€ข Mentor and guide analysts, supporting onboarding, skill development, and continuous learning across career stages.
โ€ข Conduct workload planning, prioritization, and resource allocation to support multiple concurrent initiatives.
โ€ข Build and sustain a highโ€‘performing team culture rooted in collaboration, quality, accountability, and innovation.
โ€ข Lead and oversee large scale analytical and AI initiatives, including data acquisition, transformation, modeling, AI system development, automation, and insight generation.
โ€ข Provide technical oversight and review of analytical approaches, models, and AI systems to ensure sound methodology, reproducibility, and scientific rigor.
โ€ข Guide the development and application of advanced statistical, machine learning, and AI-driven solutions, including predictive models, computer vision, large language models (LLMs), and agent-based systems.
โ€ข Lead the design and oversight of AI-enabled systems, including prompt engineering strategies, retrieval-augmented generation (RAG), embeddings, and agentic workflows.
โ€ข Establish and evolve analytical and AI best practices, documentation standards, and technical frameworks across the team.
โ€ข Ensure standards for model and AI system validation, monitoring, evaluation, documentation, and responsible AI use are consistently applied.
โ€ข Partner with engineering, IT, and data platform teams to enable scalable, reliable, and well governed solutions.
โ€ข Own delivery outcomes for data science and AI workstreams, ensuring solutions meet quality, performance, and business expectations.
โ€ข Translate business objectives into clear analytical and AI priorities, balancing near term delivery with long term capability building.
โ€ข Oversee planning, prioritization, and resourcing across projects and teams.
โ€ข Monitor solution performance, validation results, and model or AI system stability; guide troubleshooting of complex data, model, or AI issues.
โ€ข Ensure solutions are productionized effectively, with clear ownership, monitoring, and integration into business workflows.
โ€ข Establish, refine, and enforce standards for documentation, reproducibility, quality assurance, and governance.
โ€ข Remove obstacles, manage risks, and ensure consistent execution across initiatives.
โ€ข Serve as a primary point of contact for business and functional leaders on analytics and AI initiatives.
โ€ข Partner with stakeholders to define business questions, success metrics, analytical frameworks, and delivery expectations.
โ€ข Coordinate work across teams, offices, and disciplines to ensure alignment of analytical and AI approaches and outcomes.
โ€ข Communicate progress, risks, and results clearly to both technical and non technical audiences.
โ€ข Evaluate and recommend adoption of new data sources, technologies, and analytical and AI tools.
โ€ข Contribute to enterprise level analytics and AI strategy, including identifying high impact use cases and guiding their transition from concept to production.
Qualifications:
Required:
โ€ข 8 years of relevant experience required.
โ€ข Experience in data analytics, statistics, data science, AI, financial consulting, computer science or related field required.
โ€ข Experience with APIs, web scraping, SQL/no-SQL databases, and cloud-based data solutions required.
โ€ข Supervisory experience required.
โ€ข Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.
Preferred:
โ€ข Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred.
โ€ข Masters in a Data Science/Analytics/AI is a plus
Company:
CLA exists to create opportunities for our clients, our people, and our communities through industry-focused wealth advisory, outsourcing, audit, tax, and consulting services. Founded in 1998, the company is headquartered in Alpharetta, USA, with a team of 5001-10000 employees. The company is currently Late Stage.