Data Scientist

This role is for one of the Weekday's clients

Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA)

Requirements

Key Responsibilities

• Own the complete data science workflow including problem framing, feature engineering, model development, validation, and deployment planning
• Develop and operationalize machine learning models for forecasting, personalization, churn prediction, attribution, ranking, and content intelligence
• Build content and audience intelligence using NLP techniques such as embeddings, semantic similarity, topic and entity modeling, summarization, and relevance scoring
• Design sales and advertising analytics solutions including demand forecasting, pricing optimization, uplift modeling, and campaign effectiveness measurement
• Perform advanced statistical analysis including causal inference, A/B testing, experiment design, incrementality, and uplift measurement
• Partner with data engineering teams to develop scalable data pipelines and model training workflows
• Define and maintain unified KPIs and measurement frameworks to evaluate content performance and audience behavior across platforms
• Monitor model performance, detect drift, ensure robustness, fairness, and governance of deployed models
• Deliver executive-ready insights through dashboards, automated reports, and clear data storytelling
• Collaborate with cross-functional teams to prioritize initiatives with the highest business impact
• Contribute to code and design reviews, mentor peers, and raise analytical standards across the organization
  

Required Skills & Experience

Must-Have

• 4-7 years of applied data science experience delivering measurable business impact
• Strong proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and SQL
• Hands-on experience building and validating ML models including regression, classification, forecasting, clustering, recommendation systems, uplift models, and NLP-based solutions
• Solid foundation in statistics, probability, hypothesis testing, experimental design, and causal inference
• Experience working with large-scale datasets and cloud platforms such as AWS, Azure, or GCP
• Familiarity with BI and visualization tools like Tableau, Power BI, or Plotly
• Strong analytical thinking, communication, and data storytelling skills
  

Good-to-Have

• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Exposure to big data technologies like Spark, Hadoop, or Databricks
• Familiarity with MLOps practices, model monitoring, and production ML workflows
  

Education

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
  

Key Skills

• Python
• Pandas
• NLP
• Machine Learning
• SQL
• AWS
• Statistics
• Experimentation