Job Summary

To lead advanced data science initiatives, develop predictive models, and drive data-driven decision-making by extracting meaningful insights from complex datasets, enabling business growth and innovation.

Key Responsibilities

1. Develop and deploy machine learning models, predictive analytics, and AI solutions to solve business challenges.
2. Design and optimize algorithms for data processing, feature engineering, and pattern recognition.
3. Lead data exploration, mining, and visualization to uncover trends and actionable insights.
4. Collaborate with cross-functional teams to integrate data science solutions into business strategies.
5. Drive innovation by leveraging advanced statistical techniques, deep learning, and big data technologies.
6. Ensure data integrity, governance, and best practices in model development and deployment.
7. Mentor junior data scientists and promote a data-driven culture within the organization.
8. Stay ahead of industry trends and emerging technologies to enhance analytical capabilities.

Skill Requirements

2 immediate openings for 2 Data Scientist in DG (1 onsite and one offshore). Can you pls help in getting this. This can be data entry in DG. Job Description: Senior Data Scientist Position Title: Senior Data Scientist Location: [Nashville / Hybrid / Remote]

Role Summary We are seeking a highly skilled Senior Data Scientist with strong experience in cloud-based data platforms (Google Cloud or similar), Python/PySpark development, and advanced time-series forecasting. The ideal candidate will have deep supply chain domain expertise—preferably in Demand Forecasting—and a proven track record of building, training, and operationalizing predictive models at scale. This role will also focus on identifying data anomalies, creating alerting frameworks, and improving model accuracy through metric evaluation and tuning. 

Key Responsibilities 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. • Ensure forecasting models align with operational realities and business processes.

Required Qualifications • Bachelor’s or Master’s 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. • Strong communication skills with experience presenting insights to senior stakeholders.

Other Requirements

Preferred Qualifications
• Experience in retail, supply chain, inventory, or demand forecasting systems.
• Exposure to MLOps practices (CI/CD, model monitoring, retraini