What are the responsibilities and job description for the Data Scientist position at Randstad Digital?

job summary:

The Common Data Platform (CDP) team manages 100TB of data from across the client, serving economists, executives, and policy makers. We're adding AI/ML capabilities to transform how our organization extracts insights from documents, detects anomalies, and empowers decision-making.

As our Data Scientist, you'll be the AI/ML subject matter expert, splitting your time between:

- 50% - Consulting with internal teams (economists, analysts) to design and implement AI solutions for their use cases

- 25% - Building and maintaining CDP's core AI/ML models and frameworks

- 25% - Providing technical support and troubleshooting for AI/ML systems

You'll work in a collaborative environment using cutting-edge technologies including Databricks, AWS, Collibra, DataMesh architecture, and PySpark to build scalable, production-

ready AI systems.

This is a foundational role - you'll establish our MLOps practices, GenAI frameworks, and production AI capabilities from the ground up in a highly regulated Federal environment.

Required Skills - - Education: Master's degree in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field

- Experience: 4 years in data science, ML engineering, or AI development roles

- Production ML: Proven track record building and deploying ML/AI models in production environments

- Programming: Strong Python proficiency; experience with SQL and at least one statistical language (R, Stata, Matlab, Sparkly R)

- ML Frameworks: Hands-on experience with modern ML frameworks (scikit-learn, TensorFlow, PyTorch, Hugging Face)

- Generative AI: Practical experience with LLMs, RAG architectures, and prompt engineering

- Document AI: Experience processing and extracting insights from unstructured documents at scale

- Cloud Platforms: Working knowledge of AWS AI/ML services (SageMaker, Bedrock preferred)

- Communication: Ability to explain complex AI concepts to non-technical stakeholders and translate business problems into technical solutions

- Tooling: Experience working with our tech stack Databricks, AWS AI/ML tools, Starburst is preferred

Job Duties - Consulting & Enablement (50%)

- Your number one job will be to help advise economists and business teams on appropriate modeling approaches based on their use cases

- Advise on appropriate modeling approaches for diverse scenarios: RAG/knowledge bases, anomaly detection, document understanding, audit analysis

- Bridge the gap between econometric models (R, Stata) and production ML pipelines

- Review and provide feedback on AI/ML architectural proposals

- Train data engineers and business users on AI/ML best practices

Model Development (25%)

- Build production-ready AI systems for document processing (PDFs, XLSX, DOCX, CSV etc.,)

- Develop and deploy 1-2 RAG/knowledge base systems in first year

- Create reusable GenAI frameworks and patterns for the organization

- Implement solutions using AWS AI services (Bedrock, SageMaker, Textract, Databricks etc.,)

- Ensure models meet explainability requirements for regulated environments

MLOps & Support (25%)

- Establish MLOps framework and model deployment patterns

- Troubleshoot model performance issues (accuracy, latency, cost)

- Act as escalation point for AI/ML technical issues

- Train the Users by providing models and documentation as well as consulting

- Monitor and maintain production models

- Stay current on AI/ML techniques and Federal regulatory requirements

- Help other Support Team members advance their knowledge of Data Science and modeling

Job Requirements - The Common Data Platform (CDP) team manages 100TB of data from across the Federal Reserve, serving economists, executives, and policy makers. We're adding AI/ML capabilities to transform how our organization extracts insights from documents, detects anomalies, and empowers decision-making.