Data Scientist

Title:
Data Scientist (Databricks / Python / PySpark)

Location:
Deerfield, IL (Days onsite negotiable during contract ~4 days/week to convert to FTE)

Duration & Type
: Initial 7-month Contract with likely chance for extension or conversion

Compensation:
Competitive hourly W2 rate ($52.35 – $52.70), Access to Healthcare & Dental Insurance Plan of Choice
(details available upon request)
Summary
Chamberlain Advisors is seeking a Data Scientist to support a high-priority supply chain optimization and demand forecasting initiative within a large, enterprise retail and healthcare organization. This role focuses on applying advanced analytics, machine learning, and time-series forecasting techniques to improve inventory planning, drug demand forecasting, and operational decision-making across the supply chain.

The Data Scientist will work in a cloud-based Databricks environment, partnering closely with business stakeholders to respond to analytical requests, develop forecasting models, and deliver actionable insights. This is a hands-on, applied data science role with direct business impact. Click
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What You Will Be Accountable For

• Apply statistical analysis, data analytics, and machine learning techniques to solve complex business problems related to supply chain optimization and forecasting
• Perform exploratory data analysis and feature engineering on large, high-dimensional datasets
• Design, build, and evaluate time-series forecasting models and predictive models to support inventory and demand planning
• Develop and refine tree-based machine learning models (e.g., XGBoost) and other analytical approaches as appropriate
• Utilize Python, PySpark, and SQL within Databricks to process and analyze large-scale datasets
• Respond to frequent ad-hoc analytical and reporting requests from business stakeholders
• Validate model performance and interpret results for both technical and non-technical audiences
• Collaborate with data engineering, analytics, and business teams to operationalize insights
• Document analytical approaches, assumptions, and findings clearly and concisely

What Qualifications You Need

• Bachelor's degree in Computer Science, Software Engineering, or a related field
• 5–7 years of experience in data science, advanced analytics, or applied machine learning roles
• Strong proficiency in Python for data analysis and modeling
• Hands-on experience with Databricks in a cloud environment
• Strong PySpark and SQL skills for large-scale data processing and analytics
• Experience building time-series forecasting models and applied machine learning solutions
• Solid understanding of statistics, probability, and model evaluation techniques
• Ability to clearly communicate analytical findings to business and technical stakeholders
• Self-directed, adaptable, and comfortable working in a fast-paced, request-driven environment
• Preferred / Nice-to-Have
• Experience with Azure-based data platforms
• Familiarity with supply chain, inventory optimization, retail, or healthcare data
• Exposure to MLOps concepts such as model monitoring and retraining
• Experience working in large enterprise or regulated environments

Why Work with Chamberlain?
Chamberlain Advisors is a veteran-owned business that provides human capital solutions across a wide range of industries and engagement types. Chamberlain candidates benefit from our unique hiring and interviewing process which has been designed to increase the likelihood that they will be successful in their job searches. This is achieved through our 5-step recruitment process, ensuring a top-of-the-line candidate experience. Find out what makes us different; apply to Chamberlain today.

Equal Employment Opportunity
Chamberlain Advisors provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, Chamberlain Advisors complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall,