This role is for one of the Weekday's clients
Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA)
Min Experience: 4 years
Location: Bangalore
JobType: full-time
We are looking for a Data Scientist to lead the end-to-end data science lifecycle—from problem definition and hypothesis development to model deployment planning and performance evaluation. This role focuses on building scalable, production-ready machine learning solutions that drive insights across content, audience, growth, and revenue use cases.
You will work closely with product, editorial, growth, sales, and engineering teams to identify high-impact opportunities and translate complex data into actionable business outcomes.
Requirements
Key Responsibilities
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Own the complete data science workflow including problem framing, feature engineering, model development, validation, and deployment planning
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Develop and operationalize machine learning models for forecasting, personalization, churn prediction, attribution, ranking, and content intelligence
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Build content and audience intelligence using NLP techniques such as embeddings, semantic similarity, topic and entity modeling, summarization, and relevance scoring
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Design sales and advertising analytics solutions including demand forecasting, pricing optimization, uplift modeling, and campaign effectiveness measurement
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Perform advanced statistical analysis including causal inference, A/B testing, experiment design, incrementality, and uplift measurement
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Partner with data engineering teams to develop scalable data pipelines and model training workflows
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Define and maintain unified KPIs and measurement frameworks to evaluate content performance and audience behavior across platforms
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Monitor model performance, detect drift, ensure robustness, fairness, and governance of deployed models
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Deliver executive-ready insights through dashboards, automated reports, and clear data storytelling
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Collaborate with cross-functional teams to prioritize initiatives with the highest business impact
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Contribute to code and design reviews, mentor peers, and raise analytical standards across the organization
Required Skills & Experience
Must-Have
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4-7 years of applied data science experience delivering measurable business impact
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Strong proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and SQL
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Hands-on experience building and validating ML models including regression, classification, forecasting, clustering, recommendation systems, uplift models, and NLP-based solutions
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Solid foundation in statistics, probability, hypothesis testing, experimental design, and causal inference
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Experience working with large-scale datasets and cloud platforms such as AWS, Azure, or GCP
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Familiarity with BI and visualization tools like Tableau, Power BI, or Plotly
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Strong analytical thinking, communication, and data storytelling skills
Good-to-Have
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Experience with deep learning frameworks such as TensorFlow or PyTorch
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Exposure to big data technologies like Spark, Hadoop, or Databricks
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Familiarity with MLOps practices, model monitoring, and production ML workflows
Education
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Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
Key Skills
Data Science
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Python
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Pandas
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NLP
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Machine Learning
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SQL
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AWS
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Statistics
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Experimentation