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Data Science Manager Jobs in Texas (NOW HIRING)

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 ...

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 ...

They are looking for a Director of Data Science to design and operationalize quantitative models that enhance intelligence solutions for transportation, while managing a data science team and ...

They are looking for a Director of Data Science to design and operationalize quantitative models that enhance intelligence solutions for transportation, while managing a data science team and ...

Guide the end-to-end data science lifecycle for key product features; oversee experimentation ... Collaborate closely with product managers, audit subject matter experts, and engineering teams to ...

... managing direct reports as business needs evolve. Design and execute statistical modeling and ... Required : • A Master's degree in Data Science, Statistics, Mathematics, Economics, Computer ...

Project Manager, AI and Data Science

Houston, TX · Hybrid

$49.50 - $66.75/hr

We are hiring a Project Manager, AI & Data Science, who will act as both Scrum Master for the Data Science team and Project Manager for SaaS AI products such as ChatGPT Enterprise, Veo 3, Slack AI ...

We are hiring a Project Manager, AI & Data Science, who will act as both Scrum Master for the Data Science team and Project Manager for SaaS AI products such as ChatGPT Enterprise, Veo 3, Slack AI ...

Manage a team of data scientists, providing coaching, mentorship and performance management, and fostering a culture of curiosity and continuous learning * Solution delivery: Oversee end-to-end ...

Help shape standards for model lifecycle management, MLOps, analytics engineering, and AI solution ... You make data science more accessible to the business through better tools, communication, and ...

Help shape standards for model lifecycle management, MLOps, analytics engineering, and AI solution ... You make data science more accessible to the business through better tools, communication, and ...

Showing results 41-60

Data Science Manager information

See Texas salary details

$28.9K

$90.5K

$160.2K

How much do data science manager jobs pay per year?

As of Aug 12, 2026, the average yearly pay for data science manager in Texas is $90,505.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,500.00 and $116,900.00 per year, depending on experience, location, and employer.

What does a data science manager do?

As a Data Science Manager, your daily responsibilities typically include overseeing a team of data scientists and analysts, setting project priorities, and ensuring the timely delivery of data-driven solutions. You will often collaborate with cross-functional teams, such as engineering, product, and business stakeholders, to define problems, scope solutions, and communicate analytical insights. Your role also involves mentoring team members, reviewing code and analysis, and driving best practices in data science methodologies. This position requires balancing technical project oversight with team leadership and strategic business alignment.

What is a data science manager?

A Data Science Manager leads a team of data scientists to develop and implement data-driven solutions for business challenges. They oversee project timelines, ensure the quality of data analysis, and collaborate with cross-functional teams to drive decision-making. In addition to technical expertise, they require strong leadership, communication, and strategic thinking skills. Their role bridges the gap between data science initiatives and business objectives, ensuring the team's work aligns with company goals.

What is the role of a data science manager?

A data science manager oversees data science teams, guiding project priorities, setting strategic goals, and ensuring the effective use of data analysis and modeling techniques. They coordinate between technical staff and business stakeholders, often requiring skills in leadership, communication, and familiarity with tools like Python, R, or SQL. Their responsibilities include managing workflows, mentoring team members, and ensuring timely delivery of data-driven solutions.

What skills and qualifications are needed to be a data science manager?

To thrive as a Data Science Manager, you need strong analytical skills, experience in machine learning and data analytics, and a background in statistics or computer science, often supported by an advanced degree. Familiarity with tools like Python, R, SQL, cloud platforms, and experience managing data science projects are highly valued, and certifications such as Certified Analytics Professional (CAP) can be advantageous. Excellent leadership, project management, and communication skills are crucial for guiding teams and translating technical findings for stakeholders. These abilities ensure effective team performance, successful project delivery, and the alignment of data science initiatives with organizational goals.

What are the most commonly searched types of Data Science jobs in Texas? The most popular types of Data Science jobs in Texas are:
What job categories do people searching Data Science Manager jobs in Texas look for? The top searched job categories for Data Science Manager jobs in Texas are:
What cities in Texas are hiring for Data Science Manager jobs? Cities in Texas with the most Data Science Manager job openings:
Infographic showing various Data Science Manager job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 11% Part Time, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $90,505 per year, or $43.5 per hour.

Director of Data Science

TBK Bank, SSB

Dallas, TX • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 28 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!