Data Scientist II (Finance)

As a privately held, U.S.-owned and operated company, Crowley provides services to 36 nations and island territories. Our purpose is to bravely advance what's possible to elevate people and planet, with our core values of Integrity, Sustainability and Drive guiding everything we do.

By expanding and innovating our services, we have expanded our footprint in services within the Logistics, Land Transportation, Shipping, Wind and Fuel industries. Crowley and its affiliated companies have generated more than $3.5 billion in annual revenue through our people's focus on excellence and a culture that values everyone's voices and collaboration.

To continue laying the groundwork and challenge what's possible for our business, we seek to partner with individuals ready to elevate their careers with us.

SUMMARY: Responsible for designing, developing and identifying data solutions that have direct and measurable impact on the Company's support operations.

GENERAL RESPONSIBILITIES: Provide data science solutions for business operations by monitoring trends, identifying opportunities, developing and presenting recommendations, implementing strategies, and measuring the impact. Develop queries and performs extensive programming to access, transform, and prepare data for statistical modeling. Identify and diagnose data inconsistencies and errors, documents data assumptions, and forages to fill data gaps. Develops and implements analytics that enable solutions to improve business process, to generate insights, support business goals and strategy development. Develops and implements machine learning and artificial intelligence models into production. Generates relevant, actionable insights based on iterative data analysis, translate data-driven output into business language, and to make appropriate recommendations to respective business stakeholders. Summarize analysis using a wide range of data visualization techniques to determine the types of insights derived from the product and data limitations. Build and maintain effective relationships throughout the organization, fostering communication between internal and external project stakeholders which influence key decisions across stakeholder groups. EDUCATION: Master's degree or professional qualification in computer science, data science, mathematics, industrial engineering or a related field. PhD with Data Science operations research background is preferable.

EXPERIENCE: 5 years relevant work experience in applied data science and business analysis including market competitiveness, financial analysis, transportation, and logistics network optimization. In addition, to experience with modeling linear regression, logistics regression, boosting, random trees, neural networks, ensemble methods, non-parametric statistics, probabilistic modeling, and spatial modeling.

Minimum of 5 years of hands-on experience in data science and advanced analytics, applying statistical and machine learning techniques to solve real-world business problems. Strong background in areas such as market and financial analysis, transportation efficiency, and logistics network optimization. Proven ability to build, test, and deploy models using techniques such as regression (linear/logistic), decision trees, boosting, neural networks, ensemble methods, and spatial analytics.

Experience working with structured and unstructured data to deliver insights and predictive capabilities. Familiarity with productionizing models and working in cross-functional teams to integrate data-driven solutions into business operations. Experience with LLMs and Generative AI applications such as prompt engineering, RAG (Retrieval-Augmented Generation), and building automation use cases is a strong plus.

TECHNICAL PROFICIENCY: Proficient in Microsoft Office products, including Excel, Outlook, PowerPoint, Word, Access, Visio, SharePoint, Power BI, SQL Server Analysis Services, Azure ML Studio, Microsoft Projects, or similar relational databases. Technical expertise regarding data models, database design development, data mining, SQL query language, report building and segmentation techniques.

Additional Technical Proficiencies: Proficient in Python, SQL, and data visualization tools such as Power BI. Experienced in building and deploying machine learning models, statistical analysis, and predictive modeling. Skilled in working with relational and cloud databases including Snowflake. Experience with cloud platforms (Azure, AWS), version control (Git), and MLOps for scalable, production-ready deployments. Nice to have Hands-on experience with LLMs and Generative AI, including prompt engineering, RAG workflows, and model fine-tuning.

COMPETENCIES: Ability to communicate effectively verbally and in writing, including the ability to convey technical information to technical and non-technical users. Ability to establish and maintain effective working relationships. Ability to function effectively with, or as part of a team. Ability to prioritize, organize and perform multiple work assignments simultaneously. Ability to effectively manage projects that may vary in nature and scope. Ability to identify and understand complex problems and review related information to evaluate options and implement solutions. Ability to collect, organize, analyze and disseminate significant amounts of information accurately and with attention to detail. Ability to develop, improve and streamline processes to meet established goals and objectives. Ability to prepare clear and concise reports, policies, procedure, correspondences and other written materials. Knowledge of methods to collect data, research and present. Knowledge of data analysis techniques and methodology.

OTHER: Preferred certifications in Machine Learning & Artificial Intelligence, Advanced analytics, database management, cloud computing and/or ETL processes.

JOB SCOPE: Position impacts multiple business units/segments.

WORKING CONDITIONS: Normal office environment with little exposure to excessive noise, dust, temperature and the like. Extended use of a computer keyboard, viewing of a computer monitor and the ability to sit for long periods of time.