3 Model Design Jobs

Data Scientist 2-Digital Banking Kotak 811-Regional Sales Role: Data Scientist 2 Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 4- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 5- Have worked across end to end in model design, development, validation, documentation & deployment. 6- Create great data stories with expertise in robust EDA and statistical inference

Key responsibilities: 1- Development of Predictions Model using ML algorithms in entire customer journey and life cycle (Acquisition, Behaviour, Collections, Propensity, Marketing, Fraud, etc.) 2- Design and Strategy Development to offer best in class Assets Products to customers. 3- Building Prediction Model using big data from digital signals, alternate data and beyond. 4- Partnering, exploring and expanding solutions with different data providers and Companies. 5- Ownership and Responsibility to lead/manage large scale projects/model Development & Deployment. Skill Sets & key requirements: 1- Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 2- Should have worked in Banking/Fintech domain in Credit/Fraud Risk with strong understanding of Bureau Data & in-house banking Data. 3- Advance Coding skills with at least one of these- Python/SQL/Pyspark languages 1- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. 2- Have worked across end to end in model design, development, validation, documentation & deployment. 3- Create great data stories with expertise in robust EDA and statistical inference

Experience: 5+years Location: Bengaluru Role Overview We are looking for a Senior Data Engineer who will play akey role in designing, building, and maintaining data ingestion frameworks andscalable data pipelines. The ideal candidate should have strong expertise inplatform architecture, data modeling, and cloud-based data solutions to supportreal-time and batch processing needs. What you'll be doing: Design, develop, and optimise DBT models to support scalable data transformations Architect and implement modern ELT pipelines using DBT and orchestration tools like Apache Airflow and Prefect Lead performance tuning and query optimization for DBT models running on Snowflake, Redshift, or Databricks Integrate DBT workflows & pipelines with AWS services (S3, Lambda, Step Functions, RDS, Glue) and event-driven architectures Implement robust data ingestion processes from multiple sources, including manufacturing execution systems (MES), Manufacturing stations, and web applications Manage and monitor orchestration tools (Airflow, Prefect) for automated DBT model execution Implement CI/CD best practices for DBT, ensuring version control, automated testing, and deployment workflows Troubleshoot data pipeline issues and provide solutions for optimizing cost and performance. What you'll have: 5+ years of hands-on experience with DBT, including model design, testing, and performance tuning 5+ years of Strong SQL expertise with experience in analytical query optimization and database performance tuning 5+ years of programming experience, especially in building custom DBT macros, scripts, APIs, working with AWS services using boto3 3+ years of Experience with orchestration tools like Apache Airflow, Prefect for scheduling DBT jobs Hands-on experience in modern cloud data platforms like Snowflake, Redshift, Databricks, or Big Query Experience with AWS data services (S3, Lambda, Step Functions, RDS, SQS, CloudWatch) Familiarity with serverless architectures and infrastructure as code (CloudFormation/Terraform) Ability to effectively communicate timelines and deliver MVPs set for the sprint Strong analytical and problem-solving skills, with the ability to work across cross-functional teams. Nice to have Experience in hardware manufacturing data processing Contributions to open-source data engineering tools Knowledge of Tableau or other BI tools for data visualization Understanding of front-end development (React, JavaScript, or similar) to collaborate effectively with UI teams or build internal tools for data visualization