Principal Data Scientist - Generative AI, Machine Learning, Python, R - Remote

Lensa; Saint Petersburg (FL); Remote; USD 120,000 - 160,000; Full time

Job summary

A leading company is seeking a Principal Data Scientist specializing in Generative AI and Machine Learning. This remote role involves overseeing data science projects, mentoring a team, and driving data initiatives aligned with business goals. The ideal candidate will possess extensive experience in healthcare or related fields and have a strong technical background in Python, R, and machine learning frameworks. Responsibilities include deploying AI models, conducting data analysis, and collaborating with cross-functional teams to enhance operational efficiency.

Qualifications

• 10+ years’ experience as a data scientist, preferably in healthcare.
• Proficiency in Python and R; experience with frameworks like TensorFlow, Keras, PyTorch.

Responsibilities

• Oversee data science projects and manage a team.
• Lead the development and implementation of data models.
• Extract insights from complex datasets and inform strategic decisions.

Skills

Critical Thinking

Problem Solving

Data Visualization

Machine Learning

Statistical Methods

Education

Master’s Degree in Computer Science

Master’s Degree in Data Science

Master’s Degree in Statistics

Tools

Python

R

TensorFlow

Keras

PyTorch

Hadoop

Spark

SQL

NoSQL

ETL

Job description

Principal Data Scientist - Generative AI, Machine Learning, Python, R - Remote

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Job Description

Job Summary

Responsible for overseeing data science projects, managing and mentoring a team, and aligning data initiatives with business goals. Lead the development and implementation of data models, collaborate with cross-functional teams, and stay updated on industry trends. Ensure ethical data use and communicate complex technical concepts to non-technical stakeholders. Lead initiatives on model governance and model operations to meet regulatory and security requirements. This role requires technical expertise, strategic thinking, and leadership to drive data-driven decision-making within the organization and pioneer generative AI healthcare solutions, aimed at revolutionizing healthcare operations and enhancing member experience.

Job Duties

• Research and Development: Stay current with AI and machine learning advancements; apply insights to improve existing models and develop new methodologies.
• AI Model Deployment, Monitoring & Governance: Deploy models into production, monitor performance, and ensure compliance with governance and regulatory standards.
• Innovation Projects: Lead pilot projects testing new AI technologies within the organization.
• Data Analysis and Interpretation: Extract insights from complex datasets, identify patterns, and inform strategic decisions.
• Machine Learning Model Development: Design, develop, and train models using various algorithms including supervised, unsupervised, deep learning, and reinforcement learning.
• Agentic Workflows Implementation: Develop workflows utilizing AI agents for autonomous tasks to improve operational efficiency.
• RAG Pattern Utilization: Use retrieval-augmented generation techniques to enhance language model performance with external knowledge.
• Model Fine-Tuning: Adapt pre-trained models to specific tasks for optimal performance.
• Data Cleaning and Preprocessing: Prepare data for analysis by cleaning, handling missing values, and removing outliers.
• Collaboration: Work with cross-functional teams to integrate AI solutions into systems.
• Documentation and Reporting: Document models and methodologies; communicate findings to stakeholders.
• Mentorship: Guide and coach junior data scientists.
• Partner with business teams to develop ML models that improve key metrics like star ratings and care gaps.
• Present analytical insights clearly to all audience levels and manage analytical project delivery.
• Identify data and technology solutions to meet evolving business needs.
• Leverage industry trends to extract insights using various tools and techniques.

Job Qualifications

Required Education: Master’s Degree in Computer Science, Data Science, Statistics, or related field

Required Experience/Skills:

• 10+ years’ experience as a data scientist, preferably in healthcare, but other industries considered
• Knowledge of big data tools (e.g., Hadoop, Spark)
• Familiarity with relational databases and SDLC concepts
• Strong critical thinking skills for unstructured problems
• Proficiency in Python and R; experience with frameworks like TensorFlow, Keras, PyTorch
• Understanding of statistical methods and machine learning algorithms
• Experience designing agentic workflows and RAG techniques
• Expertise in fine-tuning models
• Data visualization skills (e.g., Tableau, Power BI)
• Database management experience (SQL, NoSQL, ETL)
• Strong problem-solving skills

Preferred Education

PHD or additional experience

Preferred Experience

• Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio)
• Knowledge of NLP and computer vision techniques