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Part Time Data Scientist information

See Spring, TX salary details

$33.4K

$109.2K

$174.9K

How much do part time data scientist jobs pay per year?

As of May 30, 2026, the average yearly pay for part time data scientist in Spring, TX is $109,224.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,700.00 and $121,000.00 per year, depending on experience, location, and employer.

What Does a Part Time Data Scientist Do?

A part-time data scientist’s skills and responsibilities are very similar to those of a data analyst. Like a data analyst, you have to collect and review company or industry data and then perform an analysis based on a business question the company wants to answer. You share this information with other parts of the enterprise. Where data scientists’ duties are different is that you use past data to build machine learning models. These machine learning models make predictions, and the goal is to identify trends that lead to a more thorough understanding of the business and its customers.

What are the key skills and qualifications needed to thrive as a Part Time Data Scientist, and why are they important?

To thrive as a Part Time Data Scientist, you need strong analytical skills, proficiency in statistics, and experience with data modeling, typically supported by a degree in a quantitative field. Familiarity with tools like Python, R, SQL, and data visualization platforms, as well as knowledge of machine learning libraries, is often required. Excellent problem-solving, time management, and communication skills help you effectively deliver insights and collaborate despite reduced hours. These skills ensure you can provide high-impact, actionable analyses efficiently within a limited work schedule.

How does working part-time as a data scientist typically impact project involvement and collaboration with full-time team members?

As a part-time data scientist, you may be assigned to specific projects or tasks that fit within your available hours, often focusing on defined deliverables or analytical support roles. Collaboration with full-time colleagues is common, usually through regular meetings, shared documentation, and communication tools to ensure alignment. It's important to clearly communicate your schedule and capacity, as timely updates and hand-offs help maintain project momentum. While you might not be involved in every stage of a project, your specialized contributions are highly valued, and many organizations foster flexible, inclusive environments to integrate part-time professionals effectively.

What is a part time data scientist?

A part time data scientist is a professional who applies statistical analysis, machine learning, and data processing skills to extract insights from data, but works fewer hours than a full-time employee—typically under 35 hours per week. Part time data scientists may work for one or more companies, often on flexible schedules or as contractors. Their responsibilities can include data cleaning, building predictive models, and presenting data-driven insights to help organizations make informed decisions. This role is ideal for those seeking work-life balance, students, or professionals looking to supplement their income.

What is the difference between Part Time Data Scientist vs Data Analyst?

AspectPart Time Data ScientistData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's degree in Data Analysis, Statistics, or related field
Work EnvironmentFlexible hours, project-based, often remoteOffice or remote, regular hours, structured projects
Employer & Industry UsageTech companies, startups, consulting firmsBusiness, finance, marketing, healthcare
Common Search & ComparisonPart Time Data Scientist vs Data Analyst

Part Time Data Scientists focus on advanced analytics, machine learning, and modeling, often requiring higher technical skills and specialized knowledge. Data Analysts typically handle data cleaning, reporting, and visualization. While both roles analyze data, Part Time Data Scientists work on complex models and predictive analytics, whereas Data Analysts focus on descriptive insights. The choice depends on your skills and career goals within data roles.

More about Part Time Data Scientist jobs
What are the most commonly searched types of Data Scientist jobs in Spring, TX? The most popular types of Data Scientist jobs in Spring, TX are:
What are popular job titles related to Part Time Data Scientist jobs in Spring, TX? For Part Time Data Scientist jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Part Time Data Scientist jobs in Spring, TX look for? The top searched job categories for Part Time Data Scientist jobs in Spring, TX are:
What cities near Spring, TX are hiring for Part Time Data Scientist jobs? Cities near Spring, TX with the most Part Time Data Scientist job openings:
Part Time Data Scientist jobs near you
Infographic showing various Part Time Data Scientist job openings in Spring, TX as of May 2026, with employment types broken down into 100% Part Time. Highlights an 82% In-person, 4% Hybrid, and 14% Remote job distribution, with an average salary of $109,224 per year, or $52.5 per hour.
Data Scientist, Upstream Operations

Data Scientist, Upstream Operations

ExxonMobil

Spring, TX • On-site

Part-time

Medical, Dental, Vision, Life, Retirement

Posted 20 days ago

ExxonMobil rating

6.1

Company rating: 6.1 out of 10

Based on 220 frontline employees who took The Breakroom Quiz

57th of 74 rated oil and gas companies

Job description

What role you will play in our team
  • Work on complex data science and AI/ML use cases focused on upstream oil & gas operations - from ideation and discovery through deployment and sustainment - as part of integrated, enterprise-level teams.
  • Collaborate with ExxonMobil operations engineers, field personnel, and subject matter experts to drive data-driven decision-making across upstream production and operational workflows.
  • Support the transition and integration of upstream digital analytics capabilities into the Modeling, Optimization, and Data Science (MODS) organization, ensuring continuity and enhancement of existing solutions.

What you will do
  • Lead the design, development, and deployment of advanced AI/ML solutions for upstream oil & gas operations, including production optimization, predictive maintenance, anomaly detection, and operational efficiency improvements.
  • Analyze production data, well performance metrics, sensor/IoT data, and operational logs to identify patterns, forecast outcomes, and uncover opportunities for value creation.
  • Collaborate with cross-functional teams - including production engineers, reservoir engineers, and field operations staff - to translate operational challenges into mathematical frameworks and data-driven solutions.
  • Build and deploy end-to-end AI/ML solutions in one or more upstream operations domains, applying best practices for data quality, explainability, and governance.
  • Develop GenAI applications (chatbots, copilots, multi-agent workflows) and/or time series, optimization, or predictive analytics models tailored to upstream operational needs.
  • Apply domain knowledge and physical principles to improve model accuracy and reliability in production and operations contexts.
  • Ensure production readiness through MLOps practices (CI/CD, MLflow, monitoring, cost optimization).
  • Work closely with business stakeholders to understand operational problems, communicate analytical findings, and drive adoption of data science solutions.
  • Contribute to the migration and enhancement of upstream digital analytics (UDA) tools, models, and workflows into the MODS framework.
  • Mentor peers and contribute to internal AI capability building.

About you
Minimum Skills & Qualifications:
  • 5+ years of direct experience delivering production AI/ML solutions, preferably in an upstream oil & gas or heavy industrial operations environment.
  • Experience applying data science to upstream operations workflows, including production monitoring, well performance analysis, equipment reliability, process optimization, or operational planning.
  • Demonstrated ability to work directly with business and operations teams to identify opportunities, scope analytical solutions, and deliver measurable impact.
  • Strong foundations in statistics, probability, and algorithm design.
  • Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn); experience with Databricks/Spark.
  • Familiarity with GenAI frameworks (LangChain, Promptflow) and/or optimization libraries.
  • Experience with MLOps, model governance, and explainable AI techniques (e.g., SHAP, LIME).
  • Excellent communication, collaboration, and problem-solving skills.

Preferred Knowledge & Skills:
  • Experience in the energy industry, specifically in upstream production operations, thermal/heavy oil operations (e.g., SAGD, CSS), or similar asset-intensive environments.
  • Cloud platforms (Azure ML, Azure OpenAI, Databricks).
  • Knowledge graphs, hybrid search/RAG, and semantic technologies.
  • Experience with time series analysis, anomaly detection, or predictive maintenance solutions for industrial operations.
  • Familiarity with production data systems (e.g., SCADA, PI/OSIsoft, production databases).
  • Agile development and software engineering best practices.

Educational Background Recommended:
  • Master's or PhD in Data Science, Computer Science, Engineering, Applied Math, or related field.

Your benefits
An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life.
We offer you:
  • Pension Plan: Enrollment is automatic and at no cost to you. The basic benefit is a monthly annuity to be paid to you in retirement for the rest of your life.
  • Savings Plan: You can contribute between 6% and 20% of your pay and are encouraged to enroll right away. If you contribute at least 6% to your savings plan, the Company will contribute a 7% match.
  • Workplace Flexibility: We have several programs such as "Flex your Day", providing ad-hoc flexibility around when and where you work, as well as longer-term programs such as leaves of absence and part-time work.
  • Comprehensive medical, dental, and vision plans.
  • Culture of Health: Programs and resources to support your wellbeing.
  • Employee Health Advisory Program: Provides confidential professional counseling for you and your family, including tools and resources promoting mental health and resiliency at no additional cost to you.
  • Disability Plan: Income replacement for when you cannot work due to illness or injury occurring on or off the job. Enrollment is automatic and at no cost to you.
  • More information on our Company's benefits can be found at www.exxonmobilfamily.com
  • Please note benefits may be changed from time to time without notice, subject to applicable law.

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