Senior Data Scientist

Senior Data Scientist

At Jacobs, we're challenging today to reinvent tomorrow by solving the world's most critical problems for thriving cities, resilient environments, mission-critical outcomes, operational advancement, scientific discovery and cutting-edge manufacturing, turning abstract ideas into realities that transform the world for good.

Jacobs is actively seeking an experienced Senior Data Scientist to join the Advisory Solutions Group, specifically within the Asset Management Digital Strategies Practice focusing on Federal clients. This role combines predictive modeling, statistical analysis, machine learning, and data mining with consulting-style collaboration across the Federal market. The Senior Data Scientist will help build analytical models that improve understanding of business systems, strengthen asset management strategies, and support data-driven decisions. The role will contribute to Digital Strategies activities, long-term Sales Data Science initiatives, and client-facing delivery efforts involving Federal and international stakeholders.

Key Responsibilities

• Lead the development of predictive models and machine learning solutions for business systems, asset management, sales, and commercial use cases.
• Apply regression, classification, segmentation, forecasting, clustering, and other statistical modeling techniques as appropriate.
• Explore, clean, transform, and analyze structured and unstructured data from multiple internal and external sources.
• Build repeatable data-mining processes, including data sourcing, data scraping where appropriate, feature engineering, modeling, validation, and evaluation.
• Use Python and data science libraries such as pandas, NumPy, scikit-learn, SciPy, Matplotlib, Seaborn, and Plotly.
• Develop, optimize, and maintain data models, dashboards, reports, and interactive decision-support tools.
• Design and improve data pipelines, database structures, APIs, data integrations, and analytical workflows.
• Support Digital Strategies activities using the Microsoft Azure technology stack; experience with Palantir Foundry is advantageous.
• Support long-term Sales Data Science initiatives, including model development, statistical analysis, forecasting, and performance measurement.
• Establish data-quality, validation, documentation, and governance practices to improve the reliability and responsible use of analytical products.
• Translate business questions into analytical approaches, explain results clearly, and make practical, actionable recommendations.
• Work closely with Federal clients, consulting teams, and multidisciplinary project groups.
• Contribute to workshops, technical discussions, requirements gathering, delivery planning, and client presentations.
• Document assumptions, methodologies, model performance, limitations, and recommendations to support responsible use of data science solutions.
• Review analytical methods, code, visualizations, and reports to ensure quality and alignment with project objectives.
• Lead analytical workstreams and provide mentoring and technical guidance to mid and junior analysts and data scientists.
• Contribute to proposals, business development activities, technical presentations, and reusable analytical solutions.
• Stay current with developments in data analytics, asset management, cloud technologies, artificial intelligence, and machine learning.

Here's What You'll Need

• Typically 5 or more years of experience in data science, advanced analytics, data analysis, business intelligence, or a related field.
• Demonstrated experience leading analytical projects or workstreams from requirements gathering through implementation, delivery, and client adoption.
• Bachelor's or Master's degree in Data Analytics, Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Asset Management, or a closely related discipline.
• Strong Python skills and practical experience with pandas, NumPy, scikit-learn, SciPy, and related data science libraries.
• Experience developing regression models, statistical models, segmentations, forecasting solutions, and machine learning applications.
• Strong understanding of statistics, exploratory data analysis, feature engineering, model evaluation, and performance measurement.
• Experience with data-mining processes, data preparation, data sourcing, and data scraping.
• Ability to work with messy, real-world business data and convert it into reliable and useful analytical outputs.
• Advanced proficiency with SQL and relational databases, including data modeling, transformations, joins, query optimization, and data validation.
• Experience developing dashboards, reports, and data visualizations using Power BI, Tableau, Matplotlib, Seaborn, Plotly, or comparable tools.
• Experience working with large, complex, and distributed datasets from multiple systems and sources.
• Experience with data pipelines, APIs, cloud data platforms, or enterprise data integrations.
• Experience working in consulting or client-facing delivery environments.
• Strong English communication skills and confidence working with all internal stakeholders, Federal clients, and nontechnical audiences.
• Ability to translate ambiguous business questions into structured analytical approaches and practical recommendations.
• Demonstrated ability to communicate technical concepts, analytical findings, assumptions, and limitations clearly.
• Proven ability to manage competing priorities, meet deadlines, and maintain high-quality deliverables in a fast-paced consulting environment.
• Demonstrated experience mentoring mid and junior staff and providing technical leadership within multidisciplinary teams.
• Ability to travel up to 20% of the time CONUS and OCONUS, with the ability to obtain a U.S. Government Common Access Card.
• Must be a United States Citizen, as this role involves government-facing work. Visa sponsorship is not available.

Ideally, You'll Also Have

• Experience with Microsoft Azure and Azure-based data, analytics, and AI services.
• Hands-on experience with Palantir Foundry, including data integration, ontology development, analytical workflows, model deployment, or workflow automation.
• Experience with PySpark, XGBoost, time-series forecasting, natural language processing, or semantic search.
• Experience with cloud-based data warehouses, data lakes, and enterprise analytics platforms.
• Experience supporting sales, bid, commercial, proposal, or business-performance analytics.
• Knowledge of asset management frameworks, facility condition assessments, capital planning, operations and maintenance, or lifecycle cost analysis.
• Experience developing reusable data products, analytical applications, APIs, or automated reporting solutions.
• Experience with data visualization using Matplotlib, Seaborn, Plotly, Power BI, or Tableau.
• Experience with Git, Docker, CI/CD, model deployment, or productionization of data science models.
• Familiarity with Agile, Scrum, or other iterative delivery environments.
• Experience with Jira, Confluence, Microsoft Teams, SharePoint, or comparable collaboration tools.
• Professional certifications in data analytics, business intelligence, cloud platforms, project management, data science, or asset management.
• Active or previous U.S. Government security clearance.