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Data Science Project Manager Jobs in Texas (NOW HIRING)

SolarWinds

Senior Manager, Data Science & AI

Austin, TX · On-site

As our Senior Manager of Data Science & AI, you will: * Lead a high-performing, distributed team of ... a science project. You'll combine deep Google stack expertise with a strong sense of business ...

Gartner

Sr. Data Scientist

Irving, TX · On-site

Join our fast-growing Global Product Management Data Science team and help transform Gartner ... Lead data science projects in close collaboration with Data Engineering, Application development ...

Gartner, Inc.

Sr. Data Scientist

Irving, TX · On-site

Join our fast-growing Global Product Management Data Science team and help transform Gartner ... Lead data science projects in close collaboration with Data Engineering, Application development ...

Gartner

Sr. Data Scientist

Irving, TX · On-site

Responsibilities : • Lead data science projects in close collaboration with Data Engineering ... Gartner provides fact-based consulting services, helping clients use and manage IT to enhance ...

Varsity Tutors

Data Science Tutor

Bryan, TX · Remote

$18 - $40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

Varsity Tutors

Data Science Tutor

Edinburg, TX · Remote

$18 - $40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

Varsity Tutors

Data Science Tutor

Carrollton, TX · Remote

$18 - $40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

Varsity Tutors

Data Science Tutor

Houston, TX · Remote

$18 - $40/hr

... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ... Adapts instruction using Jupyter notebooks, real-world data sets, and end-to-end project workflows ...

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All JobsData Science Project JobsData Science Project Manager JobsData Science Project Manager Jobs in Texas

Data Science Project Manager information

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How much do data science project manager jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for data science project manager in Texas is $53.58, according to ZipRecruiter salary data. Most workers in this role earn between $46.35 and $62.69 per hour, depending on experience, location, and employer.

What is the hottest job of the 21st century?

Data Science Project Managers are in high demand due to the rapid growth of data-driven decision-making across industries. They oversee data projects, coordinate teams, and require skills in analytics tools, project management, and communication. The role is considered one of the most sought-after careers in the 21st century for its impact and earning potential.

What is a Data Science Project Manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

Is 40 too late for data science?

For a Data Science Project Manager, age is not a barrier to entering or advancing in the field. Success depends on skills, experience, and continuous learning, such as mastering tools like Python or R and understanding business needs, regardless of age.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and roles in high-paying industries or senior management positions. Achieving this level often requires a combination of technical expertise, certifications, and leadership responsibilities.

How does a Data Science Project Manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

What is the difference between Data Science Project Manager vs Data Analyst?

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

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

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

Can a data scientist become a project manager?

Yes, a data scientist can become a project manager by developing skills in leadership, communication, and project planning. Gaining experience in managing teams, understanding project workflows, and obtaining certifications like PMP can facilitate this transition.
What are popular job titles related to Data Science Project Manager jobs in Texas? For Data Science Project Manager jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Texas look for? The top searched job categories for Data Science Project Manager jobs in Texas are:
What cities in Texas are hiring for Data Science Project Manager jobs? Cities in Texas with the most Data Science Project Manager job openings:
Data Science Project Manager jobs near you
Senior Manager, Data Science & AI

Senior Manager, Data Science & AI

SolarWinds

Austin, TX • On-site

Full-time

Re-posted yesterday

SolarWinds rating

8.9

Company rating: 8.9 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

34th of 209 rated software companies

Job description

At SolarWinds, we're a people-first company. Our purpose is to enrich the lives of the people we serve-including our employees, customers, shareholders, partners, and communities. Join us in our mission to help customers accelerate business transformation with simple, powerful, and secure solutions.
The ideal candidate thrives in an innovative, fast-paced environment and is collaborative, accountable, ready, and empathetic. We're looking for individuals who believe they can accomplish more as a team and create lasting growth for themselves and others. We hire based on attitude, competency, and commitment. Solarians are ready to advance our world-class solutions in a fast-paced environment and accept the challenge to lead with purpose. If you're looking to build your career with an exceptional team, you've come to the right place. Join SolarWinds and grow with us!
The Role
We are moving from traditional analytics to a Google Cloud-centric, AI-driven organization built on BigQuery, dbt, Vertex AI, and Glean.
As our Senior Manager of Data Science & AI, you will:
  • Lead a high-performing, distributed team of Data Scientists (US & EMEA).
  • Own the design and deployment of production-grade ML models and AI agents on BigQuery + Vertex.
  • Be a product-minded builder who uses AI as a lever for business productivity and automated decision-making - not as a science project.

You'll combine deep Google stack expertise with a strong sense of business impact and a bias for shipping.
Core Responsibilities
AI Strategy & Vision
  • Define and execute a Data Science & AI roadmap that integrates LLMs, GenAI, and classical ML into core functions (GTM, Product, Finance, Operations).
  • Partner with Enterprise Data, IT, and business leaders to prioritize use cases by expected impact, feasibility, and time-to-value.
  • Lean in on the rapidly changing data + AI space (Vertex, Gemini, Glean, agents) and translate platform evolution into a clear plan for SolarWinds.

Agentic Workflows & Applied LLMs
  • Lead the design of agentic workflows and AI copilots that:
  • Monitor business KPIs and health signals.
  • Perform automated root-cause exploration over governed data.
  • Push proactive, explainable "answers" and recommendations to executives and operators.
  • Use LLM orchestration, RAG over BigQuery/dbt models, and Vertex/Gemini to build agents that are grounded, auditable, and safe.

Production ML Excellence (BigQuery + Vertex)
  • Own the end-to-end lifecycle for predictive models (e.g., churn, propensity, adoption, expansion, forecasting):
  • Problem framing, feature design, model selection, evaluation.
  • Deployment on Vertex AI / BigQuery ML with robust MLOps.
  • Writebacks into BigQuery and integration into Tableau, workflows, or agents.
  • Ensure AI outputs are anchored in governed dbt models and BigQuery marts to minimize hallucination and maintain executive trust.

Team Leadership & Ways of Working
  • Recruit, mentor, and scale a world-class DS/AI team; set clear expectations for technical quality and business impact.
  • Foster a culture of "high-velocity shipping":
  • Lightweight experimentation with fast feedback loops.
  • Code reviews, reproducibility, and MLOps best practices as the norm.
  • Clear measurement of impact and iteration based on results.

Collaborate tightly with:
  • Data Engineering & Platform (BigQuery, ingestion, performance/cost).
  • Analytics Engineering & BI (semantic layer, dashboards, NLQ).
  • Data Governance & Security (policies, access, responsible AI).

Stakeholder Evangelism & Communication
  • Act as the internal "how to solve X with AI" consultant:
  • Translate ambiguous business problems into tractable DS/AI solutions.
  • Explain technical trade-offs, risks, and constraints in clear language.
  • Regularly brief GTM, Finance, Product, and Exec stakeholders on what's possible now, what's next, and what's not worth doing.

AI Innovation
  • Stay at the forefront of AI and LLM research and GCP platform capabilities (Vertex, Gemini, BigQuery ML, Glean).
  • Quickly separate hype from practical value; pilot and harden innovations that can become repeatable, governed patterns for the wider organization.

Required Experience
Experience
  • 8+ years in Data Science / Machine Learning, with 3+ years in a formal leadership role managing high-impact technical teams.
  • Proven track record of taking models and AI solutions into production and delivering measurable business outcomes (revenue, retention, efficiency, or cost).

AI & Modeling Expertise
Hands-on experience with:
  • LLM orchestration and RAG architectures (retrieval over internal data, grounding, prompt chaining).
  • Fine-tuning or adapting foundation models for business-specific contexts.
  • A broad range of statistical and ML methods across classification, regression, time-series, and uplift/propensity modeling.
  • Ability to apply these methods to large, messy real-world datasets and ship something that works now, not just in theory.
  • Deep Google Stack Experience (Required)

Significant, recent experience with Google Cloud Platform, including:
  • BigQuery for large-scale analytics, feature stores, and model inputs/outputs.
  • Vertex AI and/or BigQuery ML for model training, deployment, and monitoring.
  • Comfortable designing solutions that combine BigQuery + dbt + Vertex/BigQuery ML end-to-end.

Technical Skills
  • Strong proficiency in Python (and/or R) and SQL; familiarity with common ML frameworks.
  • Practical knowledge of MLOps patterns:
  • Model versioning, CI/CD, monitoring, retraining policies.
  • Integration of predictions and agents into production workflows and tools.

Mindset & Leadership
Strong bias for action:
  • You prefer a working prototype that solves 80% of the problem this quarter over a perfect model six months from now.
  • Demonstrated ability to:
  • Attract, grow, and retain high-caliber DS/AI talent.
  • Thrive in a fast-paced environment with evolving priorities.
  • Drive a data- and AI-informed culture across multiple functions.

Education
  • Master's or PhD in a quantitative field (CS, Statistics, Mathematics, Physics, Engineering) preferred, or equivalent deep industry experience.

If you want to shape an enterprise AI strategy on Google Cloud, lead a hands-on DS/AI team, and turn BigQuery + Vertex into real competitive advantage, we'd like to talk.
SolarWinds is an Equal Employment Opportunity Employer. SolarWinds will consider all qualified applicants for employment without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity, marital status, disability, veteran status or any other characteristic protected by law.
All applications are treated in accordance with the SolarWinds Privacy Notice: https://www.solarwinds.com/applicant-privacy-notice

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