Senior Data Scientist — Python Demand Forecasting & Machine Learning

Location: Newark, NJ | 100% Onsite, Monday–Friday

Compensation: $150,000–$250,000 | Flexibility for exceptional candidates, W2, With great benefits and awesome work enviroment.

Why This Role Exists: A growing, privately held manufacturing company is seeking a hands-on Data Scientist with strong Python, machine learning, and time-series forecasting experience. The primary focus is building predictive models that forecast physical-product demand at the SKU level, improving inventory availability, purchasing, replenishment, and manufacturing decisions. We need someone who has personally written forecasting code, developed predictive models, evaluated accuracy, and translated forecasts into real business applications. This is a hands-on technical position—not a traditional demand planning, BI reporting, or general AI/LLM role. What You Will OwnBuild and improve demand forecasting models using Python, SQL, and machine learning. Develop SKU-level forecasts using historical sales, inventory, and transactional data. Apply time-series modeling, feature engineering, seasonality analysis, and statistical forecasting methods. Evaluate forecast accuracy through backtesting, error metrics, and model comparisons. Deploy, maintain, and improve forecasting models used in operational decision-making. Partner with inventory, purchasing, and manufacturing teams to turn forecasts into measurable improvements. Improve forecast reliability, inventory efficiency, stockout prevention, and replenishment accuracy. What You NeedStrong hands-on Python experience personally developing time-series or demand forecasting models. Professional data science or machine learning experience involving real-world forecasting applications. Experience with Python, SQL, Pandas, Scikit-learn, and statistical or machine learning modeling. Practical knowledge of forecasting accuracy, time-series validation, and model performance. Ability to independently develop, troubleshoot, and improve predictive forecasting solutions. Strong analytical judgment and ability to translate technical work into business results.

Strongly Preferred: Experience forecasting physical-product demand at the SKU, item, or product-location level. Experience applying forecasts to inventory, purchasing, replenishment, or manufacturing. Experience with XGBoost, LightGBM, ARIMA, SARIMA, Prophet, or comparable forecasting approaches. Experience deploying and monitoring forecasting models in production. Background in manufacturing, retail, e-commerce, consumer goods, or supply chain. Experience with intermittent demand, large SKU portfolios, forecast bias, WAPE, or inventory optimization.

What Success Looks Like: You build reliable Python forecasting models that improve demand visibility and directly influence inventory and production decisions. Your work delivers measurable improvements in forecast accuracy, product availability, inventory efficiency, and operational performance. We are looking for someone who builds forecasting models—not someone who only consumes or reports on forecasts.