Job Title: Sr. Data Scientist
Experience: 10+ Years
Skills: Data Scientist, Python/PySpark , AWS, SQL
Locations: Alpharetta GA
We at Coforge are hiring for Sr. Data Scientist with the following skillset:
Technical skills
10+ years exp (for Data Scientist) (for Sr. DS) of which 5 years of relevant data science experience
Proven experience in developing and deploying fraud detection or risk models in AWS production environments.
Experience in
Devising creative analytical approaches to solve business problems
Developing and enhancing algorithms and models to solve business problem
Maintaining all models along with development and updating of code and process documentation
Designing data science solution approaches to unstructured problems, conducting quantitative analyses and interpreting results
Proficient in Python / PySpark programming language is a mandatory
Strong SQL, Microsoft Excel, PowerPoint skills
Data science approaches, machine learning algorithms and statistical methods.
Excellent written and verbal communication skills
Strong understanding of fraud patterns and digital transaction behaviours
Model versioning and containerization experience in AWS ecosystem, i.e., SageMaker, Docker, and EKS
Hands-on experience working within agile teams or squads on data science delivery.
Roles and Responsibilities:
Work closely with Onsite Lead, ML Engineer, Data Engineers, and QA and client stakeholders to produce end-to-end pipelines that deliver business value to client Fraud Ops
Design and develop fraud and scams detection models tailored to digital and card transaction data.
Lead feature engineering, feature selection, and hyperparameter tuning for model optimization.
Collaborate with business stakeholders, engineers, and squad members from initial discovery to deployment.
Articulate design choices, modelling approaches, and monitoring strategies effectively.
Develop and maintain ML pipelines for model training, evaluation, deployment, and monitoring in AWS.
Deploy and manage ML models using AWS SageMaker, Lambda, Step Functions, and API Gateway.
Optimize ML models for scalability, performance, and cost-efficiency in a cloud environment.
Deploy models into production using modern MLOps practices.
Implement A/B testing and performance evaluation metrics for optimal model effectiveness.
Drive reduction in false positives/negatives relative to benchmark
Qualifications: Graduate or Postgraduate from a reputed institute
