Job Description

Role Summary

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We are looking for a Senior Data Scientist with solid hands-on experience in machine learning, deep learning, predictive modeling, and customer intelligence models such as affinity, propensity, and lookalike models. The ideal candidate should be comfortable working with large-scale datasets, building production-ready models, and collaborating with business, product, engineering, and marketing teams to drive measurable impact. The role also requires exposure to Agentic AI, including AI agents, LLM-based workflows, tool-using agents, and automation frameworks.

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Key Responsibilities

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● Build, validate, and deploy machine learning and deep learning models for business use cases.

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● Develop affinity, propensity, recommendation, segmentation, churn, and lookalike models to improve targeting, personalization, and conversion.

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● Work on end-to-end data science projects, including problem framing, data exploration, feature engineering, model development, evaluation, and deployment support.

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● Analyze customer behavior, transaction patterns, content consumption, campaign responses, and digital engagement signals.

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● Collaborate with product, marketing, business, and engineering teams to translate business problems into scalable data science solutions.

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● Design experiments, A/B tests, uplift models, and measurement frameworks to assess model and campaign impact.

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● Build scalable data pipelines and reusable modeling frameworks in partnership with data engineering teams.

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● Apply deep learning techniques where relevant, including neural networks, embeddings, sequence models, NLP, or transformer-based models.

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● Explore Agentic AI use cases such as AI assistants, workflow automation, autonomous task execution, and LLM-powered decision support.

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● Present insights, model outcomes, and recommendations to technical and non-technical stakeholders.

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● Mentor junior data scientists and help improve data science best practices.

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Required Skills and Experience

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● 5+ years of experience in data science, machine learning, or applied AI roles.

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● Strong hands-on experience with ML algorithms such as regression, classification, clustering, random forests, gradient boosting, XGBoost, LightGBM, CatBoost, and ensemble methods.

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● Experience building propensity models, affinity models, lookalike models, segmentation models, and recommendation systems.

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● Good understanding of deep learning concepts and practical exposure to TensorFlow, PyTorch, Keras, or similar frameworks.

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● Strong programming skills in Python and strong SQL skills for working with large datasets.

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● Experience with data science libraries such as pandas, NumPy, scikit-learn, statsmodels, XGBoost, and LightGBM.

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● Experience with model evaluation metrics such as AUC, precision, recall, F1-score, lift, gain, KS, RMSE, MAE, and business KPIs.

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● Understanding of feature engineering, feature selection,



model interpretability, and model monitoring.

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● Exposure to cloud platforms such as AWS, GCP, or Azure is preferred.

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● Exposure to Agentic AI, LLMs, prompt engineering, RAG, LangChain, LangGraph, CrewAI, AutoGen, OpenAI APIs, or similar frameworks.

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● Ability to communicate complex analytical concepts clearly to business stakeholders.

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Preferred Qualifications

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● Experience in digital, media, e-commerce, subscription, advertising, fintech, or consumer-tech domains.

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● Experience with personalization, audience intelligence, marketing analytics, campaign optimization, or customer lifecycle modeling.

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● Exposure to MLOps tools such as MLflow, Airflow, Docker, Kubernetes, Kubeflow, Git, and CI/CD pipelines.

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● Experience with vector databases, embeddings, RAG pipelines, or LLM-based applications.

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● Understanding of data privacy, responsible AI, model governance, and ethical AI practices.

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Educational Qualification

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● Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related field.

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● Advanced degree or relevant certifications in AI/ML will be an advantage.

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Key Competencies

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● Strong analytical and problem-solving mindset.

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● Business-first approach to data science.

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● Ability to work independently and manage multiple projects.

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● Strong stakeholder management and communication skills.

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● Curiosity to explore emerging AI technologies, especially Agentic AI and LLM-based systems.

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● Ability to mentor and guide junior team members.

📌 Data Scientist (New Delhi)
🏢 HT Digital Streams
📍 New Delhi