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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** TEKSYSTEMS INC. - **Location:** Philadelphia, PA, United States (Remote available) - **Experience:** Expert - **Salary:** $145,600.0 - $156,000.0 - **Contract:** Temporary to permanent - **Skills:** Business Analytics Applications, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Data Transformation, Decision Support Systems, Network Topologies, Integer Programming, Python (Programming Language), Linear Programming, Machine Learning, Performance Tuning, Software Deployment, Software Engineering, SQL Databases, Feature Engineering, Sql Optimization, Prophet, Model Validation, Xgboost, Data Pipelines - **Published:** October 20, 2026 - **Apply:** https://www.careercircle.com/jobs/all/all/usa/pa/philadelphia/a53768bd-78b4-42b2-9e92-35804d766ff6 ## About the Role 6+ years of experience in Operations Research, supply chain optimization, data science and forecasting, including direct ownership of MEIO or comparable inventory optimization solutions and demand forecasting models. Demonstrated ability to translate business requirements, planning policies, and operational constraints into mathematical optimization and analytical solutions. Experience developing and deploying optimization models using Gurobi preferred, or comparable commercial solvers. Strong understanding of multi-echelon inventory optimization, including safety stock, service levels, demand and lead-time variability, replenishment policies, and network topology. Strong foundation in data science and forecasting, including time-series and ML-based forecasting techniques such as ARIMA, Prophet and XGBoost. Experience applying machine learning and predictive analytics to real-world supply chain problems. Experience with stochastic optimization, robust optimization, scenario planning, or simulation. Proficiency in Python and optimization frameworks such as gurobipy, Pyomo and similar OR Tools, with strong software development practices. Advanced SQL skills, including ETL, data transformation, and development of model-ready datasets. Experience with commercial MEIO platforms or comparable in-house optimization solutions. Strong understanding of supply chain planning, inventory management, and S&OP processes. Skills & Competencies Strong technical expertise in mathematical optimization, solver tuning, model validation, and forecasting. Strong data science skills, including time-series forecasting, machine learning, feature engineering, and model evaluation. Ability to connect data, models, business processes, and operational outcomes to develop scalable solutions. Strong leadership and communication skills, with the ability to influence stakeholders and explain technical concepts to diverse audiences. Ability to operationalize solutions through governance, monitoring, documentation, and user adoption. Strong project management and problem-solving skills with the ability to manage complex, cross-functional initiatives. Industry experience in consumer goods, retail, manufacturing, or distribution networks with complex demand, inventory, service, and lead-time requirements preferred. Job Type & Location, Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors. ## Description Xgboost Planning Research Equities Operations Leadership Governance Scalability Forecasting Simulations Time Series Supply Chain Data Science Benchmarking Safety Stock Communication Data Modeling Data Pipelines Demand Sensing Problem Solving Demand Planning Business Process Machine Learning Model Validation Data Engineering Network Topology Anomaly Detection Scenario Analysis Scenario Planning Project Management Influencing Skills Advanced Analytics Business Valuation Demand Forecasting Nodes (Networking) Data Preprocessing Linear Programming Operationalization Operations Research Data Transformation Feature Engineering Integer Programming Inventory Management Software Development Statistical Analysis Lifecycle Management Predictive Analytics Business Requirements Supply Chain Planning Full Stack Development Business Transformation Stochastic Optimization Decision Support Systems Applied Machine Learning Supply Chain Optimization Mathematical Optimization SQL (Programming Language) Extract Transform Load (ETL) Python (Programming Language) Continuous Improvement Process Time Series Analysis And Forecasting Autoregressive Integrated Moving Average (ARIMA), Needs a combination of Data Science (model prediction) and Operation Research (optimization, how can we do better with what we have). Develop and deploy time-series forecasting and machine learning models to improve demand planning across products, regions, and business segments. Key Deliverables: Develop and maintain SQL-based ETL processes and data pipelines supporting optimization models, scenario analysis, and production deployment. Partner with data engineering teams to ensure the quality, availability, and integrity of model inputs, including demand variability, lead times, network structure, service policies, and operational constraints. Establish governance, monitoring, and documentation to ensure model outputs are accurate, explainable, auditable, and production-ready. Contact Supplier, Forecasting - Data Science Develop and deploy time-series forecasting and machine learning models to improve demand planning across products, regions, and business segments. Build ML solutions for demand sensing, anomaly detection, predictive analytics, and forecast improvement. Perform feature engineering, model development, validation, and statistical analysis using large-scale supply chain data. Design and implement end-to-end data science pipelines, from data preparation through deployment, monitoring, and continuous improvement. Evaluate model performance using accuracy, bias, SMAPE, forecast attainment, and other relevant metrics. Collaborate with multiple teams to productionize and scale data science solutions. Inventory Optimization - MEIO Model Development & Ownership Lead the end-to-end development and ownership of Multi-Echelon Inventory Optimization (MEIO) models across retail stores, distribution centers, hubs, and customer-facing nodes. Translate business requirements, inventory policies, service objectives, and operational constraints into mathematical optimization models and scalable decision-support solutions. Design and maintain model objectives, assumptions, constraints, and optimization logic to balance service, inventory, safety stock, leadtime variability, capacity and cost. Own model lifecycle management, including design, development, validation, deployment, monitoring, and recalibration as business conditions evolve. Partner with business stakeholders to align model outputs with planning strategies, inventory policies, and service objectives. Optimization & Solver Engineering Develop mathematical optimization models using Gurobi or comparable commercial solvers. Apply techniques including linear programming, mixed-integer programming, scenario analysis, and uncertainty-aware optimization. Improve model performance through reformulation, decomposition, heuristics, and solver parameter tuning. Establish practices for reproducible testing, scenario analysis, benchmarking, and validation to ensure optimization recommendations are practical and implementable. Data, Operationalization & Adoption Develop and maintain SQL-based ETL processes and data pipelines supporting optimization models, scenario analysis, and production deployment. Partner with data engineering teams to ensure the quality, availability, and integrity of model inputs, including demand variability, lead times, network structure, service policies, and operational constraints. Establish governance, monitoring, and documentation to ensure model outputs are accurate, explainable, auditable, and production-ready. Support algorithmic planning and predictive scenario analysis using supply chain planning systems and advanced analytics tools. Drive adoption through user training, workshops, documentation, and ongoing support for planners and other stakeholders.