Description :
Job Title : Senior Data Scientist
Company : Fanatics
Location : Hyderabad, India
Experience : 5+ Years
Employment Type : Full-Time, On-site
About Fanatics :
Fanatics is a leading global digital sports platform that is redefining the way fans engage with their favorite teams and leagues across commerce, collectibles, and digital experiences. We leverage data, technology, and innovation to create a seamless experience for millions of fans worldwide.
As part of our rapidly growing Data Science & Analytics team, we are looking for a Senior Data Scientist to design and deploy predictive, optimization, and forecasting models that power critical business decisions across supply chain, inventory management, and operations.
Role Overview :
The Senior Data Scientist will play a pivotal role in building scalable and production-ready models that drive operational excellence, inventory optimization, and demand forecasting. You will work on challenging data science problems involving large-scale data, modern ML techniques, and optimization algorithms collaborating closely with cross-functional teams across engineering, product, and business functions.
Key Responsibilities :
1. Modeling & Forecasting :
- Develop, validate, and deploy predictive models for key supply chain and inventory initiatives.
- Design and enhance forecasting models for demand planning, product lifecycle, and logistics optimization.
- Apply supervised, unsupervised, and time series modeling techniques (regression, classification, clustering, etc.).
2. Optimization & Simulation :
Build and refine optimization models for network design, inventory allocation, sourcing, and fulfillment.Apply discrete optimization (MIP, constraint solvers) and simulation-based modeling to evaluate business trade-offs.Use heuristic and metaheuristic approaches to tackle complex supply chain problems efficiently.3. Exploratory Analysis & Feature Engineering :
Conduct exploratory data analysis (EDA) to identify key drivers, detect patterns, and guide model development.Develop and validate new features and variables to enhance model accuracy and interpretability.4. Time Series Modeling :
Design, test, and deploy time series forecasting models using statistical and machine learning techniques such as ARIMA, Prophet, LSTM, XGBoost, and DeepAR.Implement scalable forecasting frameworks for operational and financial planning.5. Cross-Functional Collaboration :
Partner with engineering, product, and operations teams to translate business problems into data science solutions.Present model insights, recommendations, and results to technical and non-technical stakeholders in a clear and actionable manner.6. Tooling, Automation & Deployment :
Build and maintain automated model pipelines, integrating with enterprise systems via APIs and cloud services.Leverage Python, Spark, and SQL to process, transform, and analyze large-scale datasets.Work with cloud-based infrastructure (AWS, GCP, or Azure) for scalable model deployment and monitoring.Required Qualifications :
Education : Bachelors or Masters degree in Data Science, Computer Science, Statistics, Operations Research, Mathematics, or related field.
Experience : 5+ years of experience building, deploying, and maintaining models in production environments.
Technical Expertise :
Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) and SQL.Experience with Spark, Databricks, or other distributed data frameworks.Hands-on experience with machine learning algorithms - regression, classification, clustering, and dimensionality reduction.Proven background in time series forecasting, including classical and ML-based approaches.Practical experience with discrete optimization (e.g., linear programming, MIP, constraint solvers, or genetic algorithms).Familiarity with simulation models and trade-off analysis frameworks.Experience in building data visualization dashboards using Superset, Tableau, or Power BI.Preferred Skills :
Experience in supply chain analytics, inventory forecasting, or logistics optimization.Exposure to cloud-based ML platforms (AWS Sagemaker, Azure ML, GCP Vertex AI).Knowledge of software engineering principles, version control (Git), and CI / CD practices for ML.Ability to work with large-scale, messy, and heterogeneous datasets.Strong problem-solving mindset, creativity, and attention to detail.Soft Skills :
Excellent verbal and written communication skills to present complex insights in a simple, compelling way.Strong collaboration skills to work effectively with cross-functional teams.Self-motivated, curious, and passionate about leveraging data to drive business outcomes.Why Join Fanatics :
Be part of a global leader at the intersection of sports, technology, and commerce.Opportunity to work on high-impact data science initiatives driving tangible business results.Collaborative, innovative, and inclusive work culture.Competitive compensation and benefits package.Exposure to cutting-edge ML technologies and large-scale datasets.Keywords : Data Science, Machine Learning, Forecasting, Optimization, Python, Spark, SQL, Time Series, Supply Chain Analytics, Deep Learning, Regression, ARIMA, LSTM, XGBoost, Tableau
(ref : hirist.tech)