Posted:1 day ago|
Platform:
Work from Office
Full Time
About the Company:
Our client is a leading digital media and technology organization operating at a large scale in the US market. They build trusted platforms that power content, analytics, and digital distribution and are now expanding their engineering presence in India.
Role Overview:
The ideal candidate is passionate aboofut experimentation, machine learning, and building scalable data and ML solutions. You will collaborate with engineering, product, editorial, sales, and analytics teams to translate complex, ambiguous business challenges into measurable, data-driven outcomes.
Key Responsibilities:
Lead the full data science lifecycle: problem framing, hypothesis development, feature engineering, model development, validation, and deployment planning.
Develop and operationalize machine learning models across forecasting, personalization, churn prediction, attribution, ranking, and content intelligence.
Build content and audience intelligence using NLP techniques such as embeddings, semantic similarity, topic/entity modelling, summarization, and relevance scoring.
Create sales and advertising analytics, including demand forecasting, pricing optimization, uplift modelling, and campaign effectiveness measurement.
Conduct advanced statistical analysis, causal inference, A/B testing, uplift/experiment design, and incrementality measurement.
Develop scalable data pipelines and training workflows in partnership with data engineering teams.
Build unified, cross-platform KPIs and measurement frameworks to evaluate content performance and audience behaviour.
Evaluate model performance, monitor drift, establish governance, and ensure robustness and fairness of deployed models.
Deliver clear, executive-ready insights through dashboards, automated reports, and data storytelling.
Work closely with product, editorial, growth, and sales teams to prioritize high impact opportunities.
Contribute to code and design reviews, mentor teammates, and elevate analytical rigor across the organization.
Required Skills:
Must-Have:
4-7 years of applied Data Science experience delivering measurable business impact in media, consumer analytics, advertising, or adjacent fields.
Strong proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and SQL.
Hands-on experience building, validating, and deploying ML models (regression, classification, uplift, forecasting, clustering, recommendation, NLP).
Strong foundation in statistics, probability, hypothesis testing, experimental design, and causal inference.
Experience working with large-scale datasets and cloud platforms (AWS, Azure, or GCP).
Familiarity with BI tools such as Tableau, Power BI, or Plotly for insight communication.
Excellent analytical thinking, communication, and data storytelling skills with the ability to simplify complexity for business stakeholders.
Good-to-Have:
Experience with deep learning frameworks (TensorFlow, PyTorch) or advanced NLP/ML techniques.
Exposure to big data technologies (Spark, Hadoop, Databricks).
Experience with MLOps pipelines, model monitoring, and production ML workflows.
Background in digital media, personalization systems, recommendation engines, or audience analytics.
Eligibility / Qualifications:
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