About this opportunity
Spectraforce Technologies lists this Data Scientist opportunity in newark, New Jersey. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Job Titile-: Data Scientist
Duration : 6-month contract with potential for full-time conversion
Location -: Newark, NJ (Hybrid)
Department : Data Science Team - Long-Term Care (Fraud, Waste, and Abuse Detection)
Descritption-:
The team is seeking a Data Scientist with strong MLOps and full-stack data experience, capable of both developing models and supporting production deployment within an AWS environment.
Key Focus Areas: Fraud, Waste, and Abuse (FWA) detection in long-term care
Strong understanding of business processes and ability to translate data insights into business logic
Emphasis on candidates who can learn and adapt to new business contexts
Technical Requirements
Core Skills: Programming: Python (required)
MLOps / Full-Stack Data Science: Experience in deploying machine learning models to production
Proficiency in containerization (Docker, etc.)
Working knowledge of AWS (specifically SageMaker, pipelines, access management)
Understanding of machine learning pipeline orchestration
Preferred Tools/Platforms: AWS ecosystem (SageMaker, Bedrock, etc.)
Exposure to LLMs (Large Language Models) or generative AI is a plus
Nice-to-Have: Background or understanding of insurance or healthcare data
Hands-on experience with fraud detection systems
Experience & Education Education : Bachelor's degree acceptable with strong professional experience
Master's or PhD preferred but not a hard requirement
Experience Level: Approx. 3 years of relevant data science experience (Level 1 Data Scientist)
Day-to-Day Responsibilities Focus primarily on model development (core function)
Collaborate closely with machine learning engineers for production deployment
Engage in end-to-end data science processes: Data exploration and modeling
Model validation and tuning
Assisting with model deployment and monitoring
Work closely with business stakeholders to understand fraud patterns and operational nuances
Team Structure Reports to Hiring Manager
Collaborates with: Senior Data Scientists (peer mentors and project leads)
Machine Learning Engineers (for deployment/productionization)
Business partners (for domain understanding and data interpretation)
Interview Process
Three rounds total: Technical Assignment & Presentation Candidate receives a small project beforehand
Expected to present findings during interview
Technical Interview Deep-dive discussion around project and technical skills
Final Interview With Marin and other team members
Focus on team fit, communication, and business understanding
Key Insights Preference for candidates who are strong in MLOps even if slightly less advanced in pure data science theory.
The ability to grasp new business models quickly is critical, especially for FWA detection.
Ideal candidate demonstrates hands-on experience with both model building and AWS-based deployment.
Someone with experience using large language models or recent GenAI technologies would stand out.
Experience Level: 3 years (Level 1 Data Scientist)
Environment/Tools: AWS (SageMaker, Bedrock, etc.)
Programming Languages: Python required
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.