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Director Of Data Science Jobs (NOW HIRING)

TBK Bank, SSB

Director of Data Science

Dallas, TX · On-site

Director of Data Science Position Summary We are seeking a Director of Data Science to design, build, and operationalize quantitative models that power both internal and customer-facing intelligence ...

Triumph Financial

Director of Data Science

Dallas, TX · On-site

Director of Data Science Position Summary We are seeking a Director of Data Science to design, build, and operationalize quantitative models that power both internal and customer-facing intelligence ...

Hello Innovation

Director of Data Science

Detroit, MI · On-site

As our Director of Data Science you will set the foundation that powers impactful data-driven insights; harnessing the power of data to shape our products with the potential to improve the lives of ...

Coupang

Director of Data Science

Mountain View, CA

$174K - $299K/yr

Role Overview Coupang is seeking a Director of Data Science to lead high-impact, data-driven initiatives across the business. This leader will be responsible for shaping and executing data science ...

Hello Innovation

Director of Data Science

Detroit, MI · On-site

As our Director of Data Science you will set the foundation that powers impactful data-driven insights; harnessing the power of data to shape our products with the potential to improve the lives of ...

The Hartford

Director of Data Science

Hartford, CT · On-site +1

$153K - $229K/yr

The Hartford is seeking a Director of Data Science to lead the Personal Insurance modeling within the Actuarial Strategic Modeling (ASM) department. This leadership role offers a unique opportunity ...

The Hartford

Director of Data Science

Chicago, IL · On-site +1

$153K - $229K/yr

The Hartford is seeking a Director of Data Science to lead the Personal Insurance modeling within the Actuarial Strategic Modeling (ASM) department. This leadership role offers a unique opportunity ...

The Hartford

Director of Data Science

Charlotte, NC · On-site +1

$153K - $229K/yr

The Hartford is seeking a Director of Data Science to lead the Personal Insurance modeling within the Actuarial Strategic Modeling (ASM) department. This leadership role offers a unique opportunity ...

Blend

Associate Director of Data Science

$60K - $60K/yr

Responsibilities : • Lead the delivery of AI and data science projects, managing a team of 4-5 developers and data scientists. • Design and implement AI solutions leveraging advanced techniques ...

Blend360

Associate Director of Data Science

Columbia, MD · On-site +1

$58K - $59K/yr

Lead the delivery of AI and data science projects, managing a team of 4-5 developers and data scientists. * Design and implement AI solutions leveraging advanced techniques, including prompt ...

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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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Director Of Data Science jobs near you
Director of Data Science

Director of Data Science

TBK Bank, SSB

Dallas, TX • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 21 days ago

Job description

Join Triumph!
At Triumph, our vision is a world where freight transactions are accurate and seamless on the most modern and secure freight transaction network. That's why we're looking for passionate, innovative, solutions-oriented people to join our team. We thrive on providing exceptional customer service and we look for team members with an entrepreneurial spirit and a passion to build successful partnerships with our clients. Because at the end of the day our goal is to help our partners businesses run better.
Director of Data Science
Position Summary
We are seeking a Director of Data Science to design, build, and operationalize quantitative models that power both internal and customer-facing intelligence solutions. This role focuses on developing forecasting, optimization, and signal-based models that translate largescale transportation data into trusted insights for carriers, brokers, and shippers. In addition to hands-on technical leadership, this role may include managing data science talent and helping to scale the function over time as organizational needs evolve. The ideal candidate brings strong statistical rigor, experience working with real-world operational data, and a product-oriented mindset for deploying models that influence commercial and operational decisions across transportation networks.
Key Responsibilities
  • Develop and maintain forecasting and predictive models supporting transportation use cases such as pricing, demand forecasting, capacity trends, service performance, and network dynamics.
  • Build and scale the data science function, including hiring, onboarding, and managing direct reports as business needs evolve. Design and execute statistical modeling and experimentation, including hypothesis testing, A/B testing, and causal analysis to evaluate market and operational changes.
  • Build optimization and decision support models that inform routing, capacity allocation, pricing strategy, and operational trade-offs.
  • Lead signal development for transportation intelligence products, transforming raw transactional and network data into scalable, reliable indicators and indices.
  • Establish and lead model validation, performance monitoring, and governance frameworks to ensure stability, accuracy, and trustworthiness of production models.
  • Partner closely with product, analytics, and engineering teams to translate transportation domain needs into analytically sound, production ready models.
  • Document methodologies, assumptions, and limitations to support transparency, internal review, and customer facing confidence in intelligence outputs.
  • Continuously evaluate new data sources, modeling approaches, and techniques relevant to transportation, logistics, and network-based intelligence.

Required Qualifications
  • A Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or another relevant quantitative discipline is required.
  • 5-7 years of professional experience in data science, applied statistics, or quantitative analytics.
  • Strong experience with forecasting, predictive modeling, and statistical analysis in applied business contexts.
  • Demonstrated ability to build models that support decision making, optimization, or market intelligence.
  • Strong Python and SQL skills and experience working with large, complex datasets.
  • Experience validating models and monitoring performance in production environments. Direct experience with model governance frameworks.
  • Ability to clearly communicate quantitative insights to both technical and non-technical stakeholders.

Preferred Qualifications
  • Experience working with transportation, logistics, supply chain, or network-based data.
  • Strong expertise in
    • Regression & tree-based models (e.g., XGBoost, Random Forest)
    • Time series forecasting (e.g., SARIMAX, Prophet, TFT)
    • Statistical modeling of skewed distributions (e.g., log-normal, gamma)
  • 2 years in a leadership or people-management capacity
  • Deep understanding of freight market dynamics, including the interaction between spot and contract pricing, broker and carrier economics, and the impact of capacity cycles and seasonality on market behavior.
  • Familiarity with time-series modeling, signal processing, or index construction.
  • Experience supporting intelligence, analytics, or data products used by external customers.
  • Experience working with large-scale datasets in cloud environments and data pipelines (e.g., Snowflake, AWS, Sagemaker)

We offer Medical, Dental, Vision, Paid Time Off, 401k and much more.
Go on. Do it. Apply Today!

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