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Data Science Jobs in Wyoming (NOW HIRING)

As a Data Science Engagement Lead within the Digital Process Twin (DPT) portfolio, you will lead data scientists and collaborate with cross-functional business teams to identify transformation ...

Bachelor's degree in computer science, mathematics or scientific field requiring statistical * Hands-on ability to manipulate data and build analytical data sets * Expert proficiency in one or more ...

Bachelor's degree in computer science, mathematics or scientific field requiring statistical * Hands-on ability to manipulate data and build analytical data sets * Expert proficiency in one or more ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help ...

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Data Science information

See Wyoming salary details

$36K

$118K

$188.9K

How much do data science jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data science in Wyoming is $117,979.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,700.00 and $130,700.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
What are the most commonly searched types of Data Science jobs in Wyoming? The most popular types of Data Science jobs in Wyoming are:
What are popular job titles related to Data Science jobs in Wyoming? For Data Science jobs in Wyoming, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Wyoming look for? The top searched job categories for Data Science jobs in Wyoming are:
What cities in Wyoming are hiring for Data Science jobs? Cities in Wyoming with the most Data Science job openings:
Infographic showing various Data Science job openings in Wyoming as of August 2026, with employment types broken down into 100% Full Time. Highlights an 73% In-person, 5% Hybrid, and 22% Remote job distribution, with an average salary of $117,979 per year, or $56.7 per hour.

Data Science Engagement Lead

Shell

Shell, WY

Full-time

Posted 10 days ago


Shell rating

5.0

Company rating: 5.0 out of 10

Based on 273 frontline employees who took The Breakroom Quiz

79th of 86 rated oil and gas companies


Job description

Selangor, Malaysia


Job Family Group:

Research and Development


Worker Type:

Regular


Posting Start Date:

August 5, 2026


Business Unit:

Finance


Experience Level:

Experienced Professionals


Job Description:

What'sthe role

The Commercial Data Science (CDS) team is a community of experts partnering with Shell's business stakeholders to deliver data-driven solutions through deep process understanding and technical excellence.

As a Data Science Engagement Lead within the Digital Process Twin (DPT) portfolio, you will lead data scientists and collaborate with cross-functional business teams to identify transformation opportunities using process-centric data and guide the application of process mining, optimization, and AI/ML techniques to improve operational performance. Your work will drive measurable business outcomes by enhancing visibility, agility, and efficiency across Shell's business operations.

The DPT Centre of Excellence (CoE) aims to "Empower Process Transformation through Digital Process Twins" by applying advanced process mining and analytics capabilities. Shell is recognized as an industry leader in process mining, pioneering innovative analytical approaches and advancing the process twin concept. The CoE actively engages with academic partners, industry forums, and technology vendors to drive research, innovation, and thought leadership.

If you are passionate about applying data science to process event data to drive organizational process transformation-and value collaboration, innovation, and continuous learning-we invite you to join us as a Data Science Engagement Lead.

Whatyou'llbe doing

  • Lead process-mining consulting engagements, translating business challenges into analytical problem statements and actionable insights that drive measurable digital process transformation.
  • Partner with global and regional business stakeholders to uncover inefficiencies, define transformation opportunities, and generate process-analytics use cases aligned with the Integrated Process Plan (IPP).
  • Oversee the design and development of process data models, collaborating with process and data architects to ensure clean, integrated, and analysis-ready event data from enterprise systems (e.g., SAP, Salesforce, ServiceNow).
  • Facilitate process discovery and value workshops, translating analytical findings into tangible business outcomes through clear, evidence-based, and persuasive data storytelling.
  • Guide the delivery of analytical and AI/ML solutions, ensuring alignment with strategic priorities, technical excellence, and measurable value realization (e.g., process cycle-time reduction or cost-efficiency improvement).
  • Champion change and capability adoption, organizing enablement sessions, roadshows, and awareness programs to promote process-mining and analytics capabilities across business Region / functions.
  • Support collaboration with academic and technology partners to explore new analytical methods and contribute insights to product enhancement discussions that inform Shell's Digital Process Twin (DPT) evolution.
  • Mentor and coach data scientists, developing consulting, technical, and storytelling capabilities within the DPT community.
  • Monitor industry trends and emerging technologies to provide input on potential future use cases in process analytics, optimization, and AI.

Whatyou bring

  • 10-12 years of total experience, including 6+ years in analytics consulting, of which 3+ years in process-mining consulting or process-analytics leadership within global organizations or leading consulting firms.
  • Bachelor's or Master's degree in Mathematics, Statistics, Economics, Data Science, Engineering, Technical Finance, or a related quantitative field.
  • Combines deep analytical expertise with consulting leadership, leveraging prior hands-on experience in analytical solution development and data-driven problem solving to deliver measurable business outcomes.
  • Process-Mining Technical Expertise: Strong command of process-mining concepts, algorithms, and tools (e.g., Celonis EMS, SAP Signavio, PM4Py), with proven ability to extract, model, and interpret event-log data to uncover inefficiencies, monitor compliance, and optimize end-to-end processes.
  • Led the development and delivery of AI/ML use cases using process-centric data, integrating predictive and prescriptive models with process-mining insights to drive data-informed decisions and measurable process transformation.
  • Designed and implemented process data models and event-data integration frameworks, collaborating with process architects, data engineers, and IT teams to ensure analysis-ready, high-quality datasets across enterprise systems.
  • Delivered process-analytics and AI-driven consulting engagements across business domains such as Finance, Sales, Procurement, and Supply Chain-identifying bottlenecks, quantifying value opportunities, and achieving measurable performance improvements.
  • Champions disciplined and responsible data-science delivery, applying Agile practices, MLOps/DevOps workflows (e.g., GitHub, CI/CD), and Responsible AI (XAI) principles to ensure transparency, scalability, and measurable business outcomes across global teams.
  • Demonstrated strength in analytical storytelling, distilling complex analytical findings into persuasive narratives and visual insights that drive executive alignment and decision-making.
  • Experience in leading and active engagement in professional communities, industry forums, and technology meetups to foster collaboration, share insights, and drive innovation in analytical methods and digital transformation initiatives.
  • Proven expertise in applying process mining, optimization, machine learning, or AI techniques to process centric data for measurable business outcomes.
  • Strong proficiency in Python, SQL, and process data modeling, with experience transforming data from enterprise systems such as SAP, Salesforce, HANA, or ServiceNow.
  • Deep understanding of process data structures (case IDs, activities, timestamps, attributes) and the ability to build scalable analytics pipelines.
  • Structured, hypothesis-driven problem-solving approach with the ability to interpret and communicate analytical results clearly to diverse audiences.
  • Ability to guide cross-functional teams, ensuring analytical solutions align with business strategies and deliver measurable value.
  • Experience with cloud-based analytics environments and process-analytics platforms (e.g., Celonis EMS, SAP Signavio, Microsoft Process Mining) and familiarity with major cloud platforms (Azure, AWS, GCP).
  • Understanding of end-to-end business-process lifecycles and value-chain optimization.
  • Knowledge of process simulation, optimization, or Operations Research (OR) techniques for process improvement and decision support.
  • Strong data storytelling and visualization skills, translating complex analytics into actionable business insights.
  • Continuous-learning mindset, staying current with advances in process mining, AI/ML, and digital-twin technologies.
  • Experience with complementary or open-source process-mining tools (e.g.,PM4PY, ProM).
  • Research and innovation orientation, contributing to proofs-of-concept or publications with academic and vendor partners.

Key Competencies required for this role:

  • Analytical Consulting Execution
  • Structured Problem Solving & Critical Thinking
  • Business Partnering & Value Translation

What we offer

You bring your skills and experience to Shell and in return you work with talented, committed people on one of the most important challenges facing our planet.You'llhave the opportunity to develop the skills you need to grow in an environment where we value honesty, integrity, and respect for one another.You'llbe able to balance your priorities as you become the best version of yourself.

  • Progress as a person as we work on the energy transition together.

  • Continuously grow the transferable skills you need to get ahead.

  • Work at the forefront of technology, trends, and practices.

  • Collaborate with experienced colleagues with uniqueexpertise.

  • Achieve your balance in avalues-led culture that encourages you to be the best version of yourself.

  • Benefit from flexible working hours, and the possibility of remote/mobile working.

  • Perform at your best with a competitive starting salary and annualperformancerelatedsalary increase - our pay and benefits packagesare considered to beamong the best in the world.

  • Take advantage of paid parental leave,including fornon-birthingparents.

  • Join anorganisationworking to become one of the most diverse and inclusive in the world. We strongly encourage applicants of all genders, ages, ethnicities, cultures, abilities, sexual orientation,and life experiences to apply.

  • Grow as you progress through diverse career opportunities in national and

  • internationalteams.

  • Gain access to a wide range of training and developmentprogrammes.

We'dlike you to know that Shell has a bold goal: to become one of the world's most diverse and inclusive companies. You can get to know more about howwe'reworking towards that goal,click here.

ShellBusiness Operations (SBO)inMalaysia

Shell Business Operations (SBO) is a chain of operationalcentersthat form an integral part of Royal Dutch Shell. We influence business development for Shell globally, enabling the work of 93,000 employees in over 70 countries across the world.
SBO Kuala Lumpur is home to 11different functionsthat support Shell within the Southeast Asia,Oceania, and Middle East region. Housing more than 2000 employees, SBO Kuala Lumpur is focused on driving excellent corporate performance that enable Shell tooperatein a global competitive and ever-changing business environment.
Shell Business Operations (SBO) Kuala Lumpur is focused on driving excellent corporate performance in Contracting and Procurement, Creative Solutions, Customer Operations, Finance Operations, Human Resource, Information Technology, Legal Operations, Retail Centre of Excellence, Supply Chain, Technical Asset Operation and Upstream Transformation. We enable Shell tooperatein a global-competitive and ever-changing business environment

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DISCLAIMER:

Please note: We occasionally amend or withdraw Shell jobs and reserve the right to do so at any time, including prior to the advertised closing date. Before applying, you are advised to read our data protection policy. This policy describes the processing that may be associated with your personal data and informs you that your personal data may be transferred to Shell/Shell Group companies around the world. The Shell Group and its approved recruitment consultants will never ask you for a fee to process or consider your application for a career with Shell. Anyone who demands such a fee is not an authorised Shell representative and you are strongly advised to refuse any such demand. Shell is an Equal Opportunity Employer.

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