Senior Data Scientist

Nashville, IN - USA

Monthly Salary: Not Disclosed

Posted on: 3 hours ago

Vacancies: 1 Vacancy

Job Summary

Model Development & Forecasting
Build train and deploy time-series forecasting models using techniques such as:
o XGBoost
o Random Forest
o Linear regression based models
o ARIMA SARIMA Holt-Winters
o Prophet / FBProphet
Operationalize model pipelines using Google Cloud Platform (GCP) services (BigQuery Cloud Composer Dataproc Cloud Run) or equivalent cloud technologies (AWS Azure).
Perform feature engineering hyperparameter tuning model validation and continuous improvement of forecasting pipelines.
Data Engineering & Cloud Expertise
Develop scalable data processing workflows using Python PySpark and SQL.
Work with large datasets and cloud-native data environments for analytics and modeling.
Collaborate with data engineering teams to ensure robust data pipelines and high-quality training data.
Analytics & Anomaly Detection
Design and implement data anomaly detection systems to identify volume pattern and trend deviations.
Build automated alerting frameworks for early warning of data or forecast issues.
Investigate root causes of anomalies and recommend long term fixes.
Accuracy Metrics & Optimization
Develop and maintain accuracy measurement frameworks (e.g. MAPE RMSE MAE WAPE Bias).
Continuously fine tune and optimize model performance based on metric evaluations.
Communicate model accuracy trends and insights to both technical and business stakeholders.
Domain Expertise Supply Chain & Demand Forecasting
Apply strong domain knowledge in retail supply chain inventory planning replenishment and demand forecasting.
Partner with business teams to translate forecasting needs into data science solutions.

Required Qualifications
Bachelors or Masters degree in Data Science Computer Science Statistics Mathematics or a related field.
5 years of experience as a Data Scientist with hands-on model development.
Strong programming skills in Python including PySpark and common data science libraries (Pandas NumPy SciPy scikit learn).
Experience working with GCP or similar cloud platforms.
Hands-on experience with time-series forecasting regression models and ensemble methods.
Strong SQL experience and comfort with large-scale datasets.
Ability to diagnose data issues perform anomaly analysis and build automated alerting solutions.

Preferred Qualifications
Experience in retail supply chain inventory or demand forecasting systems.
Exposure to MLOps practices (CI/CD model monitoring retraining pipelines).

Model Development & Forecasting Build train and deploy time-series forecasting models using techniques such as: o XGBoost o Random Forest o Linear regression based models o ARIMA SARIMA Holt-Winters o Prophet / FBProphet Operationalize model pipelines using Google Cloud Platform (GCP) ser...