Data Scientist

About Us:

Apparel and Footwear

Role Overview:

The Data Scientist will be responsible for applying our pre-trained demand forecasting models to generate actionable insights and highly accurate forecasting outcomes. This role involves thorough data analysis, identifying trends and anomalies, interpreting results, and communicating findings effectively to a non-technical business audience. The ideal candidate is less focused on creating algorithms and more oriented towards solving business challenges and providing insights that make a tangible impact.

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:

  Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.