Job Title: Full Stack Data Scientist (Payments & Optimization)
Location:Alpharetta, GA(Hybrid) Client: Fiserv
Employment Type: Contract

IN- Person Interview (L2)

Job Description

Role Overview

We are seeking a Full Stack Data Scientist with strong expertise in machine learning, data engineering, and payment systems to design and deliver data-driven solutions for optimizing payment routing and transaction processing.

This role requires a combination of advanced analytics, ML model development, and hands-on data engineering skills, along with domain experience in banking or financial services, and experience deploying models using cloud-native platforms such as AWS SageMaker.

Key Responsibilities

Design, develop, and deploy machine learning models for:

Payment routing optimization
Transaction success rate improvement
Payload and cost optimization

Build, train, and deploy ML models using Amazon SageMaker

Manage end-to-end ML lifecycle (training, tuning, deployment)
Implement model versioning, monitoring, and retraining strategies

Analyze large-scale transactional datasets to identify:

Patterns, anomalies, and optimization opportunities
Fraud signals and performance bottlenecks

Build and maintain data pipelines ensuring:

Data quality, integrity, and security
Efficient data processing and transformation

Collaborate with engineering teams to integrate ML models into production systems using APIs and microservices
Work with real-time and batch processing systems for payment data
Ensure compliance with financial regulations and data security standards

Required Skills & Qualifications

6+ years of experience in Data Science, Machine Learning, or related fields
Strong expertise in machine learning model development and optimization techniques
Proficiency in programming languages:

Python (preferred)
R or Julia (nice to have)

Hands-on experience with ML frameworks:

scikit-learn
TensorFlow
PyTorch

Strong experience with Amazon SageMaker, including:

Model training and hyperparameter tuning
Deployment (endpoints, batch transform)
SageMaker Pipelines for automation
Model monitoring and lifecycle management

Strong analytical skills with the ability to work on large datasets

Domain Expertise (Must Have)

Experience working with payment systems, including:

Credit/Debit card processing
ACH transactions
Electronic payments

Understanding of:

Payment routing logic
Transaction lifecycle
Authorization and settlement flows

Data Engineering Skills

Experience building and managing:

Data pipelines
ETL/ELT processes

Experience integrating SageMaker with AWS services such as:

S3 (data storage)
Lambda (serverless processing)
Step Functions (workflow orchestration)

Knowledge of:

Data quality and validation frameworks
Data governance and security best practices

Compliance & Domain Knowledge

Familiarity with banking/financial services domain
Understanding of compliance standards such as:

PCI-DSS (Payment Card Industry Data Security Standard)

Nice to Have

Experience with real-time streaming (Kafka, Spark Streaming)
Knowledge of broader AWS ecosystem
Experience with fraud detection or risk modeling
Exposure to MLOps practices and CI/CD pipelines

Full Stack Data Scientist (Payments & Optimization)

Key skills

About this role