Data Scientist - AI and Data Science Engineer I

Deloitte•Jersey City, NJ

5d•$76,600 - $127,600•Onsite

About The Position

Our Deloitte AI & Engineering team transforms technology platforms, drives innovation, and helps make a significant impact on our clients’ success. You’ll work alongside talented professionals reimagining and reengineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation.

Requirements

Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to provide clear guidance to others
Bachelor’s degree
Experience with Python and SQL
Experience supporting healthcare applications
Experience developing, evaluating, deploying, or monitoring machine learning models
Must be able to obtain and maintain the required clearance for this role
Ability to travel 10-15%, on average, based on the work you do and the clients and industries/sectors you serve
Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Nice To Haves

Experience with natural language processing, large language models, retrieval-augmented generation, or vector databases
Experience building machine learning pipelines for data ingestion, feature engineering, training, scoring, and validation
Experience with Databricks Model Serving or comparable cloud-based model deployment technologies
Experience with MLflow or similar tools for experiment tracking, reproducibility, model versioning, and lifecycle management
Experience with continuous integration/continuous deployment, automated testing, and MLOps workflows
Experience applying privacy, cybersecurity, or regulatory considerations in healthcare or public-sector analytics use cases

Responsibilities

Conducting exploratory data analysis across structured, unstructured, text, image, and healthcare-related datasets and developing machine learning and deep learning models using Python and established data science frameworks
Supporting end-to-end machine learning pipelines, including data ingestion, preprocessing, feature engineering, model training, validation, deployment, monitoring, and performance reporting
Assisting with natural language processing, large language model, retrieval-augmented generation, vector database, and agentic AI use cases for the NextGen TSS platform and helping industrialize research models into production-ready solutions
Building reusable data preparation, model training, scoring, and validation components and deploying models using Databricks Model Serving or comparable cloud-based technologies with experiment tracking and model lifecycle management tools such as MLflow
Contributing to MLOps workflows, including continuous integration and continuous deployment, automated testing, governance, release management, documentation, platform integration, and model and pipeline troubleshooting and optimization