Key Facts

Remote From:

Full time

Mid-level (2-5 years)

English

Hard Skills

Medical Insurance Claims SQL (Programming Language) Python (Programming Language) Machine Learning Model Validation Predictive Analytics Bayesian Statistics Data Architecture Natural Language Processing (NLP) ICD 503 WAN Optimization Fraud Detection Diagnosis-Related Group Deep Learning Population Stratification Machine Learning Machine Learning Feature Engineering Risk Control Scikit-Learn (Python Package) Statistical Modeling CP System PyTorch (Machine Learning Library) Medical Record Management Data Mining Xgboost Utilization Management Provider Network Management TensorFlow Boosting Biostatistics Risk Ratings Actuarial Science Value-Based Care Economics MLOps (Machine Learning Operations) Clinical Document Architecture Epidemiology CI/CD Hl7 V2 Interoperability Cross-Functional Collaboration Stakeholder Communications

Other Skills

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Communication
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Problem Solving

Roles & Responsibilities

Strong proficiency in Python and ML libraries (scikit-learn, XGBoost, TensorFlow/PyTorch)
Hands-on experience with healthcare claims datasets and coding systems
Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques
Strong knowledge and expertise working with SQL

Requirements:

Develop, train, and deploy ML models for use cases such as claims cost prediction, utilization forecasting, fraud, waste, and abuse detection, risk adjustment and member stratification, and provider performance and network optimization
Build scalable pipelines for feature engineering, model training, validation, and monitoring using modern ML techniques (gradient boosting, deep learning, NLP, probabilistic modeling)
Analyze and interpret medical, pharmacy, and dental claims data (CPT/HCPCS, ICD-10, DRG, NDC) and translate domain knowledge into meaningful features and model strategies
Partner with clinicians, product managers, and business stakeholders to define problems, measure outcomes, and communicate complex analytical findings in clear, actionable terms

SmartLight Analytics

About SmartLight Analytics

SmartLight Analytics was formed by a group of industry insiders driven to make a meaningful impact on the rising cost of employee healthcare. Using our statistical, clinical, fraud detection, coding and claims expertise we deliver the most complete wasteful spend reduction solution directly to self-funded employers. SmartLight utilizes proprietary inferential analytics customized to your employee population, followed by expert clinical review on 100% of your medical claims. Our team partners with your TPA to implement solutions resulting in a lower per employee healthcare spend. We let your data tell us where to look without any preconceived notions about what the errors are beforehand. Our approach is low-touch and involves zero employee involvement. SmartLight consistently delivers a higher ROI compared to other cost reduction solutions on the market.

Founded: 2018

Company size: 1 - 10

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Job description

Overview

We’re seeking a Machine Learning Data Scientist with deep expertise in healthcare claims data to design, build, and deploy advanced analytics and machine learning modeling solutions. In this role, you’ll transform complex administrative and clinical datasets into actionable insights that improve cost efficiency, care quality, and operational performance across the healthcare ecosystem.

You’ll collaborate with data engineers, clinicians, and product teams to develop predictive models, optimize workflows, and support strategic decision‑making. This position is ideal for someone who thrives at the intersection of data science, healthcare operations, and modern machine learning.

Key Responsibilities

Machine Learning & Advanced Analytics

Develop, train, and deploy ML models for use cases such as:

Claims cost prediction and utilization forecasting

Fraud, waste, and abuse detection

Risk adjustment and member stratification

Provider performance and network optimization

Apply modern ML techniques including gradient boosting, deep learning, NLP, and probabilistic modeling.

Capable of applying advanced predictive analytics to correlate disparate datasets and events and derive business value.

Build scalable pipelines for feature engineering, model training, validation, and monitoring.

Healthcare Claims Expertise

Analyze and interpret medical, pharmacy, and dental claims (CPT/HCPCS, ICD‑10, DRG, NDC).

Translate domain knowledge into meaningful features and model strategies.

Cross‑Functional Collaboration

Partner with clinicians, product managers, and business stakeholders to define problems and measure outcomes.

Communicate complex analytical findings in clear, actionable terms.

Required Qualifications

Strong proficiency in Python and ML libraries (scikit‑learn, XGBoost, TensorFlow/PyTorch).

Hands‑on experience with healthcare claims datasets and coding systems.

Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques.

Strong knowledge and expertise working with SQL.

Ability to translate business needs into analytical solutions.

Must have demonstrated the ability to solve complex problems with minimal direction.

Preferred Qualifications

Experience with NLP applied to clinical notes or unstructured healthcare data.

Familiarity with actuarial concepts, risk scoring, or value‑based care models.

Familiarity deploying models into production (MLOps, CI/CD).

Background in health economics, epidemiology, or biostatistics.

Prior work with FHIR, HL7, or interoperability standards.

SmartLight Analytics was formed by a group of industry insiders who wanted to make a meaningful impact on the rising cost of healthcare. With this end in mind, SmartLight combats fraud, waste, and abuse in healthcare through our proprietary data analysis and model development. Requiring the bare minimum in employer involvement, our process works behind the scenes to save money without interrupting employee benefits or requiring employee behavior changes.

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