Coforge
Job Title:
Sr. Data Scientist
Experience:
10+ Years
Skills:
Python/PySpark, AWS, SQL
Base pay range $130,000.00/yr - $140,000.00/yr
Location: Atlanta, GA
Responsibilities
Work closely with Onsite Lead, ML Engineer, Data Engineers, QA, and client stakeholders to produce end‑to‑end pipelines that deliver business value to client Fraud Ops.
Design and develop fraud and scam detection models tailored to digital and card transaction data.
Lead feature engineering, feature selection, and hyperparameter tuning for model optimisation.
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.
10+ years of experience in data science, with at least 5 years of relevant data science experience.
Proven experience in developing and deploying fraud detection or risk models in AWS production environments.
Experience devising creative analytical approaches to solve business problems.
Experience developing and enhancing algorithms and models to solve business problems.
Ability to maintain all models along with development and updating of code and process documentation.
Proficient in designing data science solution approaches to unstructured problems, conducting quantitative analyses, and interpreting results.
Proficiency in Python/PySpark programming is mandatory.
Strong knowledge of machine learning algorithms and statistical methods.
Excellent written and verbal communication skills.
Strong understanding of fraud patterns and digital transaction behaviours.
Experience with model versioning and containerization in AWS ecosystem (SageMaker, Docker, EKS).
Hands‑on experience working within agile teams or squads on data science delivery.
Seniority Level Senior
Employment Type Full‑time
Industry IT Services and IT Consulting
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Sr. Data Scientist
Experience:
10+ Years
Skills:
Python/PySpark, AWS, SQL
Base pay range $130,000.00/yr - $140,000.00/yr
Location: Atlanta, GA
Responsibilities
Work closely with Onsite Lead, ML Engineer, Data Engineers, QA, and client stakeholders to produce end‑to‑end pipelines that deliver business value to client Fraud Ops.
Design and develop fraud and scam detection models tailored to digital and card transaction data.
Lead feature engineering, feature selection, and hyperparameter tuning for model optimisation.
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.
10+ years of experience in data science, with at least 5 years of relevant data science experience.
Proven experience in developing and deploying fraud detection or risk models in AWS production environments.
Experience devising creative analytical approaches to solve business problems.
Experience developing and enhancing algorithms and models to solve business problems.
Ability to maintain all models along with development and updating of code and process documentation.
Proficient in designing data science solution approaches to unstructured problems, conducting quantitative analyses, and interpreting results.
Proficiency in Python/PySpark programming is mandatory.
Strong knowledge of machine learning algorithms and statistical methods.
Excellent written and verbal communication skills.
Strong understanding of fraud patterns and digital transaction behaviours.
Experience with model versioning and containerization in AWS ecosystem (SageMaker, Docker, EKS).
Hands‑on experience working within agile teams or squads on data science delivery.
Seniority Level Senior
Employment Type Full‑time
Industry IT Services and IT Consulting
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