Data Scientist

2 days ago

Bengaluru, Karnataka, India beBeeDataScience Full time ₹ 1,80,00,000 - ₹ 2,50,00,000

Drive Business Outcomes with Data Science Expertise

We are seeking an accomplished data scientist to leverage their expertise in machine learning and statistical analysis to drive business decisions.

  • Data Analysis: Conduct thorough data exploration, cleaning, and transformation to prepare datasets for modeling efforts, ensuring high data quality and accuracy.
  • 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.
  • 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.
Required Skills and Qualifications
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; Master's preferred.
  • 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.
  • 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.
  • Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
  • Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and statistical analysis.

The Ideal Candidate

Please note that this role requires a 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.

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