Data Scientist, hybrid | 1055900

OUR GOAL: 
Treat our consultants and clients the way we would like others to treat us!
 
Interested in joining our team? Check out the opportunity below and apply today!
  
We are seeking a Senior Data Scientist (Level II) to support high-impact AI/ML initiatives within a regulated environment. This role will focus on advancing targeting models and delivering scalable, production-ready solutions that drive business outcomes.

The ideal candidate brings strong technical depth, hands-on model development experience, and the ability to operate independently while collaborating across cross-functional teams.
 
Hybrid- M, Tues, Wed in-office 8am-5pm (flexibility needed)
 
Key Responsibilities
Model Development & Optimization

• Lead the design, development, and optimization of machine learning models to improve targeting accuracy and business performance
• Apply advanced Machine Learning and Deep Learning techniques to refine existing models and develop new solutions as needed

Feature Engineering & Data Preparation

• Design and build scalable feature pipelines, transforming raw and complex datasets into high-quality model inputs
• Work with large, messy datasets (e.g., claims data) while ensuring data integrity and usability

Production & Pipeline Scalability

• Transition analytical models and scripts into robust, production-ready pipelines
• Ensure code quality, documentation, and adherence to engineering and data science best practices
• Support model deployment, monitoring, and ongoing performance improvements

Cross-Functional Collaboration & Insight Translation

• Partner with data science, analytics, and business teams to translate business problems into technical solutions
• Communicate model methodologies, assumptions, and results clearly to non-technical stakeholders

Qualifications
Required

• Master’s or PhD in Data Science, Computer Science, Statistics, or a related field
• Minimum 5+ years of hands-on experience in data science and machine learning model development
• Proven track record of taking models from ideation through production deployment
• Strong proficiency in Python, SQL, and AWS
• Deep expertise in Machine Learning and/or Deep Learning techniques
• Experience working with large-scale, complex datasets in collaborative environments

 
Preferred

• Experience within healthcare, pharmaceutical, or other highly regulated industries
• Hands-on experience with claims data or similarly complex, regulated datasets
• Strong understanding of data privacy, compliance, and governance requirements
• Experience with MLOps practices, including pipeline automation, deployment, and monitoring

What We’re Looking For

• A self-driven, senior-level contributor who can lead model development efforts and influence technical direction
• Someone who thrives in a team environment and contributes to shared goals without needing sole ownership
• A candidate who balances technical excellence with business impact, delivering solutions that are both scalable and meaningful
• This is a Level II role, requiring demonstrated depth in both technical execution and real-world application of AI/ML solutions
• Candidates must be comfortable working in a fast-paced, collaborative, and regulated environment

Reference: 1055900
  

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Revel IT, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your experience doesn’t align perfectly with every qualification in the description, we encourage you to apply anyway. You might be the right candidate for this or our other open roles!  

Revel IT is an Equal Opportunity Employer. Revel IT does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.

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