Key Responsibilities :

- Data Analysis : Conduct in-depth data analysis to identify trends, patterns, and anomalies in demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have)

- Model Utilization : Leverage existing pre-trained forecasting models, optimizing their performance by incorporating a nuanced understanding of data points and improving model outcomes based on data insights.

- Interpretation & Communication : Interpret model results and explain outcomes in simple, actionable terms for business stakeholders, ensuring clarity and relevance.

- Insights Generation : Develop insights that guide business decisions, aiming for highly accurate forecasting outcomes to meet business requirements.

- Collaboration : Work closely with cross-functional teams, including business stakeholders and analysts, to ensure forecasting outputs align with business objectives and provide real-world value.

- Continuous Improvement : Identify opportunities to improve model performance through better data usage and fine-tuning, rather than new model development.

Required Skills & Qualifications :

- Experience : 3-6 years of experience in data science or a related field, specifically in Demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have)

- Technical Proficiency : Strong skills in data analysis, data visualization, and working with pre-trained ML models.

- Proficiency in Python, and SQL is preferred.

- Business Focus : Strong orientation towards solving business problems rather than a pure focus on machine learning algorithms.

- Communication Skills : Ability to clearly communicate insights and forecast results to non-technical stakeholders in simple, understandable language.

- Problem Solving : Demonstrated ability to interpret data, uncover actionable insights, and suggest practical solutions for business needs.

- Detail-Oriented : Thorough attention to detail, ensuring accuracy in forecasting and relevance of insights.

- Educational Background : Bachelors or Masters degree in Data Science, Statistics, Computer Science, or a related field