Data Scientist – Retail / CPG

As our Data Scientist extraordinaire, you'll be wielding the mighty powers of numbers and machine learning like a superhero! Your mission? To craft mind-blowing predictive models and algorithms that will conquer complex business challenges and leave a global footprint of awesome impact.

Responsibilities:

• Model Development: Design, develop, and implement predictive models and algorithms using advanced statistical techniques and machine learning frameworks.
• Business Impact: Collaborate with stakeholders to understand business objectives, identify key metrics, and ensure model outcomes align with strategic goals and drives measurable impact.
• Data Analysis: Conduct thorough data exploration, cleaning, and transformation to prepare datasets for modeling efforts, ensuring high data quality and accuracy.
• Collaboration: Work with cross-functional teams, including engineering, product management, and business teams, to integrate models into production systems and monitor performance.
• Communication: Present findings to technical and non-technical audiences, providing actionable insights and recommendations to drive business strategy.
• Innovation: Stay up to date with the latest trends and advancements in data science and machine learning to continuously enhance modeling practices and methodologies.

Required Experience and Skills – Our Must haves

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; Master’s preferred.
• 6-8 years of experience in data science with a strong focus on model development and algorithm design in the retail domain such as Fashion or CPG.
• Experience of building Machine Learning & Deep Learning solutions in large production scale environment.

       Strong communication and requirement gathering skills from business and product teams is a must with capability of understanding complex business problems and designing right ML solutions.

       Must have deep understanding of at-least couple of Retail/CPG use cases such as customer segmentation, recommendations, demand forecasting, sentiment analysis, inventory optimization, promotion uplift modeling, campaign analysis, churn prediction etc.

       Proficiency in programming languages such as Python, and experience with data manipulation libraries (e.g., Pandas, NumPy).

       Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and statistical analysis.

Core Competencies

       Strong problem-solving skills with a proactive approach to optimisation.

       Excellent communication skills and ability to collaborate across global teams and time zones.

       Experience in designing and implementing Data Science best practices and frameworks.