Data Scientist in retail

Data Scientist in retailMust have recent Retail industry experience (or grocery specifically which would be that much better, but at least retail)Can sit 100% remote during the contract duration, but since they want to convert this person eventually, there will thenbe a 3 day / week onsite requirement. Quincy, MA or Chicago office.6 months contract to hireVideo interviewStrong with Python as a Data ScientistMust have experience working with Marketing - specifically with consumer level modelingMust have Forecasting experience - Demand or Volume ForecastingTime seriesMust have recent Retail industry experience or grocery specifically as a nice to haveKnows the whole lifecycle of whole data science project initiation to deployment, like docker CI/CD Jenkins terraformSoft skills, tech lead for a project and work with other tech teamsPyspark - Strong good to haveDatabricks - Strong good to haveThe team supports customer segmentation and modeling work. They also focus on forecasting capabilities, so they will be doing volume forecasting on several intiiativesFulfillment work - batch optimization work. Additional forecasting piece environmental friendly initiatives - plastics, carbon admission, predict healthy items. Team Environment - Adam the Director, 2 managers under him. Each manager has a team of 3.Job Description:Senior Data Scientist roleThis position will involve applying advanced analytics to extract actionable insights from complex datasets, facilitating data-driven decision-making across the organization. The Resource will design and implement predictive models, optimizing business processesthrough the development of machine learning algorithms. The focus is on delivering measurable outcomes, enhancing productivity, and improving resource allocation. The lasting impact of these contributions will be the integration of data-driven decision-makinginto the ADUSA organizational framework, positioning ADUSA at the forefront of innovation in the industry.Location: Remote PositionTasks/Deliverables• Building the production codebase for the Advanced Analytics models• Creating training pipelines• Creating inference pipelines• Apply advanced analytics for actionable insights• Implement predictive models with a focus on machine learning for optimization• Collaborate on data-driven solutions for business challengesSkills• Python, Databricks-PySpark framework• libraries: Prophet, Nixtla, itertools, scitkitlearn, etc• Data/Training pipeline development, EDA, Feature Engineering, Model delivery, etc.• Forecasting and Time Series analysisForecasting, demand forecasting, time seriesTime series is forecasting future values for product sales, product unit salesWorked in retail and groceryClassic ML/data science methodsPyspark/pythonLifecycle of whole data science project initiation to deployment, like docker CI/CD Jenkins terraformSoft skills, tech lead for a project and work with other tech teamsCoordinating that daily and managingShould be able to do own literature and be a senior

Created: 2026-05-09