Kotak

Data Scientist 3_Digital Banking Kotak 811_0434_8147_1094575

Kotak Bengaluru, Karnataka, India

Banking · 10,001+ employees

14 h ago
data-scientist Senior (5-10 yrs) Full-time India
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About the role

The Data Scientist will design, develop, and deploy advanced machine learning models to solve complex business problems and enhance customer experiences. They will also mentor junior team members and collaborate with cross-functional teams to translate business challenges into data-driven solutions.

What they look for

Python R SQL PySpark Machine Learning Predictive Analytics NLP Deep Learning Time Series Forecasting Databricks Power BI Tableau AWS Azure GCP MLOps

Requirements

Candidates must possess a Bachelor's or Master's degree in a quantitative field and 6-10 years of relevant experience in data science or advanced analytics. Strong technical proficiency in Python, SQL, and machine learning frameworks is required, along with experience in enterprise-scale model deployment.

Full description

Job Title

Data Scientist III

Department

Data Science / Analytics / Digital Transformation

Location Mumbai / Bengaluru / Hybrid

Grade

Senior Individual Contributor

Role Summary

We are seeking an experienced and highly analytical Data Scientist III to drive advanced data science initiatives and build scalable machine learning solutions that solve complex business problems. The incumbent will leverage statistical modeling, machine learning, artificial intelligence, and data engineering techniques to generate actionable insights, enhance customer experiences, optimize business processes, and support strategic decision-making. The role requires strong expertise in predictive analytics, model development, experimentation, stakeholder management, and mentoring junior data scientists while collaborating with cross-functional teams across business, product, technology, and operations.

Key Responsibilities

Data Science & Machine Learning

  • Design, develop, validate, and deploy advanced machine learning and statistical models. • Build predictive, classification, recommendation, forecasting, and optimization models. • Develop scalable AI/ML solutions to improve business performance and customer outcomes. • Conduct feature engineering, model selection, hyperparameter tuning, and performance evaluation. • Apply advanced techniques including NLP, deep learning, generative AI, and time series forecasting where applicable.

Analytics & Insights

This is a Public document. • Analyze large structured and unstructured datasets to identify business opportunities and trends. • Translate business challenges into analytical frameworks and data-driven solutions. • Develop insightful dashboards, reports, and analytical presentations for senior leadership. • Perform hypothesis testing, A/B testing, and causal impact analysis.

Model Governance & Deployment • Ensure model accuracy, fairness, explainability, and compliance with organizational standards. • Monitor model performance and retrain models as needed. • Support MLOps practices, automation, and model deployment pipelines. • Maintain proper documentation for models, methodologies, and business impact.

Stakeholder Management • Partner with business leaders to understand requirements and deliver analytical solutions. • Present findings and recommendations to senior stakeholders. • Act as a subject matter expert for advanced analytics and machine learning initiatives.

Leadership & Mentoring

  • Mentor junior data scientists and analysts. • Review analytical approaches and model outputs. • Promote best practices in statistics, machine learning, coding, and experimentation. Required Qualifications Education • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field. • PhD preferred for highly specialized domains. Experience This is a Public document. • 6-10 years of experience in Data Science, Machine Learning, Advanced Analytics, or related fields. • Proven experience in building and deploying enterprise-scale ML models. Technical Skills Programming & Tools • Python, R, SQL • PySpark, Spark • Jupyter Notebook • Git, Docker, Kubernetes Machine Learning • Supervised & Unsupervised Learning • Ensemble Models • Deep Learning • NLP • Recommendation Systems • Time Series Forecasting Cloud Platforms • AWS, Azure, or GCP • Databricks preferred Data Visualization • Power BI • Tableau • Matplotlib • Seaborn Databases • SQL Server • Oracle This is a Public document. • PostgreSQL • NoSQL Databases

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