Parker Management
Data Scientist
We are looking for a Data Scientist with expertise in optimization and forecasting to help improve how we manage labor, staffing, and operational resources across our retail locations. This role is critical in building models and decision-support tools that ensure the right people, in the right place, at the right time balancing customer service, efficiency, and cost. You will work closely with Operations, Finance, and Store Leadership teams to deliver practical solutions that improve labor planning, scheduling, and demand forecasting. The right candidate will be confident, resourceful, and excited to own both the technical and business-facing aspects of applying data science in a fast-paced retail environment. Responsibilities: Build and maintain forecasting models (time-series, machine learning, and statistical) for sales and transactions. Develop and deploy optimization models (linear/mixed-integer programming, heuristics, simulation) to improve workforce scheduling and labor allocation. Partner with operations and finance to translate forecasts into actionable staffing and labor plans that reduce costs while maintaining service levels. Build dashboards and automated tools to track forecast accuracy, labor KPIs, and staffing effectiveness. Provide insights and "what-if" scenario modeling to support strategic workforce and budget planning. Knowledge, Skills, and Abilities: Strong foundation in forecasting techniques (time-series models, regression, machine learning) and optimization methods (linear/mixed-integer programming, heuristics, simulation). Proficiency in Python or R for modeling and analysis, along with strong SQL skills for working with large-scale datasets. Knowledge of statistics, probability, and applied mathematics to support predictive and prescriptive modeling. Experience building and deploying predictive models, optimization tools, and decision-support solutions that drive measurable business outcomes. Strong data storytelling and visualization skills using tools such as Power BI, Tableau, or Looker. Ability to translate analytical outputs into clear, actionable recommendations for non-technical stakeholders. Strong collaboration skills with the ability to partner cross-functionally with Operations, Finance, and Store Leadership to drive adoption of data-driven approaches. Ability to work independently and resourcefully, combining technical depth with practical problem-solving to deliver results in a fast-paced environment. Education and Requirements: Required: Bachelor's or Master's degree in Data Science, Statistics, Applied Mathematics, Industrial Engineering, Operations Research, or related field. Minimum 2-3 years of professional experience in Data Science or a related area. Strong skills in time-series forecasting (e.g., ARIMA, Prophet, ML-based approaches). Proficiency in optimization techniques (linear programming, integer programming). Strong Python or R programming skills. SQL expertise for large, complex datasets. Strong communication skills with the ability to partner with business stakeholders. Preferred: Experience in Retail, Restaurant, and/or Convenience Stores a plus. Experience with cloud platforms (Snowflake, AWS, GCP, Azure). Knowledge of BI tools (Tableau, Power BI, Looker). Physical Requirements: Prolonged periods sitting/standing at a desk and working on a computer Must be able to lift up to 50 pounds Parker's is an equal opportunity employer committed to hiring a diverse workforce and sustaining an inclusive culture. Parker's does not discriminate on the basis of disability, veteran status or any other basis protected under federal, state, or local laws.
We are looking for a Data Scientist with expertise in optimization and forecasting to help improve how we manage labor, staffing, and operational resources across our retail locations. This role is critical in building models and decision-support tools that ensure the right people, in the right place, at the right time balancing customer service, efficiency, and cost. You will work closely with Operations, Finance, and Store Leadership teams to deliver practical solutions that improve labor planning, scheduling, and demand forecasting. The right candidate will be confident, resourceful, and excited to own both the technical and business-facing aspects of applying data science in a fast-paced retail environment. Responsibilities: Build and maintain forecasting models (time-series, machine learning, and statistical) for sales and transactions. Develop and deploy optimization models (linear/mixed-integer programming, heuristics, simulation) to improve workforce scheduling and labor allocation. Partner with operations and finance to translate forecasts into actionable staffing and labor plans that reduce costs while maintaining service levels. Build dashboards and automated tools to track forecast accuracy, labor KPIs, and staffing effectiveness. Provide insights and "what-if" scenario modeling to support strategic workforce and budget planning. Knowledge, Skills, and Abilities: Strong foundation in forecasting techniques (time-series models, regression, machine learning) and optimization methods (linear/mixed-integer programming, heuristics, simulation). Proficiency in Python or R for modeling and analysis, along with strong SQL skills for working with large-scale datasets. Knowledge of statistics, probability, and applied mathematics to support predictive and prescriptive modeling. Experience building and deploying predictive models, optimization tools, and decision-support solutions that drive measurable business outcomes. Strong data storytelling and visualization skills using tools such as Power BI, Tableau, or Looker. Ability to translate analytical outputs into clear, actionable recommendations for non-technical stakeholders. Strong collaboration skills with the ability to partner cross-functionally with Operations, Finance, and Store Leadership to drive adoption of data-driven approaches. Ability to work independently and resourcefully, combining technical depth with practical problem-solving to deliver results in a fast-paced environment. Education and Requirements: Required: Bachelor's or Master's degree in Data Science, Statistics, Applied Mathematics, Industrial Engineering, Operations Research, or related field. Minimum 2-3 years of professional experience in Data Science or a related area. Strong skills in time-series forecasting (e.g., ARIMA, Prophet, ML-based approaches). Proficiency in optimization techniques (linear programming, integer programming). Strong Python or R programming skills. SQL expertise for large, complex datasets. Strong communication skills with the ability to partner with business stakeholders. Preferred: Experience in Retail, Restaurant, and/or Convenience Stores a plus. Experience with cloud platforms (Snowflake, AWS, GCP, Azure). Knowledge of BI tools (Tableau, Power BI, Looker). Physical Requirements: Prolonged periods sitting/standing at a desk and working on a computer Must be able to lift up to 50 pounds Parker's is an equal opportunity employer committed to hiring a diverse workforce and sustaining an inclusive culture. Parker's does not discriminate on the basis of disability, veteran status or any other basis protected under federal, state, or local laws.