Fluor Corporation is hiring for an entry level Data Scientist 1 role in USA

Position:

• Data Scientist I

Company:

• Fluor Corporation

Location:

• Houston, Texas, United States

Job type:

• Full-time

Job mode:

• On-site

Job requisition id:

• 148982BR

Years of experience:

• Entry level (freshers and candidates with internship experience encouraged); 0-3 years

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Company description:

• Fluor Corporation is a globally recognized leader in engineering, procurement, construction (EPC), and maintenance services. With a strong presence across continents, Fluor is known for delivering innovative and sustainable solutions across various industries including infrastructure, energy, chemicals, and more.

• The company prides itself on nurturing a diverse and inclusive culture that values big-picture thinking and collaborative problem-solving. Its mission extends beyond project delivery—it’s also about building long-term careers and contributing to a better world.

• Employees at Fluor are exposed to complex, large-scale projects and a work environment where continuous learning and growth are encouraged. Through its commitment to safety, quality, integrity, and teamwork, Fluor provides opportunities for employees to not only shape infrastructure but also to transform their own careers.

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Profile overview:

• This entry-level Data Scientist I role is focused on analytics and involves collaborating closely with EPHD® analysts and international data science teams. The candidate will play a pivotal role in understanding Fluor’s EPC (Engineering, Procurement, and Construction) Model and contributing to various data processing and analytics tasks.

• Initially, the emphasis will be on foundational work such as preparing, extracting, transforming, and validating data. As the individual gains confidence and experience, they will progress to more complex responsibilities like developing predictive models, building smart visualizations, and integrating insights into project execution systems.

• The role includes developing systems that convert raw data into actionable intelligence. Through close coordination with global teams in India, the US, and the Philippines, the selected candidate will contribute to the development of sophisticated analytics environments and tools that support real-time decision-making.

• In addition to technical tasks, the position involves frequent communication with stakeholders from project planning, scheduling, supply chain, and engineering teams to deliver clear, meaningful insights that drive project performance improvements.

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Qualifications:

• A strong academic background in Mathematics, Statistics, or related fields, with coursework or project experience in data science and analytics.

• Exposure to data cleansing, preparation, and visualization techniques, with emphasis on working with large datasets and building descriptive and predictive models.

• Practical experience via internships or academic projects is highly appreciated, especially if it involves data analytics, predictive modeling, or machine learning.

• Familiarity with programming tools such as R, Python, and SQL is important, with bonus points for experience in JavaScript, Plotly, Shiny (now Posit), and version control tools like Git or TFS (DevOps).

• Hands-on experience with relational and non-relational databases (e.g., SQL, MongoDB) is a plus. Willingness to work with unfamiliar tools and quickly adapt to new technologies is essential.

• Capability to work with teams spread across multiple time zones including Asia, Europe, and North America, with flexibility to support off-hour meetings as required.

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Additional info:

• The role requires high collaboration and a proactive approach. Candidates must be self-starters, curious, and able to absorb and apply feedback quickly.

• Expect to participate in designing, developing, testing, and deploying analytics charts and tools using platforms like R Shiny (Posit), JavaScript, and various internal Fluor systems.

• Candidates should be comfortable working with both structured and unstructured data, creating algorithms, and engaging in exploratory data analysis to uncover insights that inform strategic decisions.

• The role involves both support and leadership over time, depending on the candidate’s growth. Opportunities to develop machine learning models using techniques like Random Forest, XGBoost, SVM, Naive Bayes, and Elastic Net may arise.

• Communication is key—whether it's documenting work, explaining complex data to non-technical stakeholders, or participating in peer reviews and quality assurance checks.

• Fluor supports a work environment that values innovation, learning, and inclusion. This position will challenge and grow the analytical and technical skills of the candidate while contributing directly to Fluor’s project outcomes.

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Core Responsibilities:

Data Engineering & Analytics Foundations

• Assist in extracting, preparing, cleaning, and transforming large datasets for use in analytics environments.

• Work with both structured and unstructured data sources to build consistent, high-quality datasets for downstream analysis.

• Engage in early-stage data QA and problem-solving to identify and resolve inconsistencies or anomalies in data pipelines.

Development of Smart Visuals & Charts

• Use R, Python, JavaScript, and proprietary tools like LWRS to design and refine smart data visualizations.

• Build interactive dashboards and analytics charts to help stakeholders understand project performance and operational patterns.

• Develop visual storytelling elements that turn raw analytics into actionable insights for project teams and leadership.

Support for Predictive Modeling

• As experience grows, support the creation and refinement of predictive models that guide critical project decisions.

• Learn to apply machine learning techniques for forecasting outcomes, identifying risk, and optimizing project planning.

• Participate in model testing, validation, and refinement, ensuring they remain accurate and reliable over time.

Project and Stakeholder Engagement

• Work alongside analysts, engineers, project managers, and IT staff to gather requirements and deliver analytics tools that meet business needs.

• Help translate complex data findings into clear recommendations, visual formats, or simulations for various project teams.

• Provide feedback loops, user training, and post-deployment support to improve data-driven decision-making processes.

Tools & Technologies Exposure

• Hands-on experience with:

  • R Studio and R Shiny (now Posit)

  • Python and relevant data science libraries

  • JavaScript and JSON for UI enhancement

  • SQL and NoSQL databases

  • Git and version control platforms like DevOps/TFS

  • Plotly, ggplot, and other charting packages

  • POSIT software for package/library management and versioning

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Key Attributes of the Ideal Candidate:

Technical Agility

• Comfortable picking up new programming languages or tools quickly, with a demonstrated ability to apply them to practical problems.

• Proficiency in querying databases, writing algorithms, and developing visual dashboards from scratch.

Problem-Solving Mindset

• Has a curious and investigative nature—digs into data problems and seeks to uncover the “why” behind anomalies or patterns.

• Uses a combination of analytical thinking and technical knowledge to build robust, scalable solutions.

Communication & Collaboration

• Can explain complex technical insights in simple terms for business users and leadership.

• Works well with global teams, manages coordination across time zones, and participates actively in team discussions.

Growth-Oriented Attitude

• Eager to learn, receive feedback, and take on more responsibility over time.

• Takes ownership of tasks, displays initiative, and supports others to deliver collective success.

Flexibility & Work Ethic

• Comfortable working on dynamic, fast-paced projects with shifting priorities.

• Maintains a strong sense of urgency, meets deadlines, and manages time efficiently.

• Resilient and adaptable—able to work independently as well as in collaborative team environments.

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Career Growth and Learning Opportunities:

• This role serves as an entry point into Fluor’s global data science ecosystem. Candidates will work on real-world challenges tied to multi-billion-dollar infrastructure and capital projects.

• Over time, strong performers will have opportunities to lead chart and model development, interface with senior stakeholders, and potentially own end-to-end analytics tools and systems.

• Candidates can expect mentorship from seasoned Data Scientists and EPHD Analysts, exposure to Fluor’s proprietary project systems, and engagement in high-value global projects.

• The position offers a pathway into advanced roles in predictive modeling, AI integration in EPC workflows, and data-driven project optimization.

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Salary & Compensation:

• Salary range: $68,000 to $118,000 annually

• Final offer may vary depending on skills, experience, location, and market conditions

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Benefits:

• Competitive benefits package includes:

  • Health, dental, and vision plans

  • Life and disability insurance

  • 401(k) retirement plan with company match

  • Paid time off (vacation, sick, holidays)

  • Parental leave and bereavement leave

  • Employee Assistance Programs (EAP)

  • Opportunities for training, certification, and career development

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Equal Opportunity Employer:

• Fluor is committed to diversity and inclusion.

• Employment decisions are made without regard to race, color, gender identity, age, religion, disability, veteran status, or any other protected status.

• All qualified individuals are encouraged to apply.

Please click here to apply.

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