Senior Data Scientist

Delta Dental of Missouri is seeking a passionate and innovative Senior Data Scientist to join our growing team and play a pivotal role in shaping the future of dental insurance through cutting-edge AI applications. The Senior Data Scientist will lead end-to-end ownership of data science projects, from problem definition and data collection to model development, deployment, and evaluation. This role will spearhead advanced data science solutions, focusing on machine learning (ML), Large Language Models (LLMs) and computer vision applications to revolutionize the insured experience and optimize claims workflows. The Senior Data Scientist is responsible for the curation, preparation, and ethical use of sensitive company data for data science applications. The position requires the ability to translate technical insights into actionable recommendations for business stakeholders and technical knowledge to train, deploy, and maintain ML models on a cloud infrastructure. Management reserves the ability to request other functions from this position. Excellent problem solving, communication, and customer service skills are a must.

Responsibilities

Technical Leadership: Provide technical expertise and guidance to internal teams on data science needs and best practices.
LLM & RAG Development: Lead the research, development, and optimization of LLM (Large Language Model) and Retrieval-Augmented Generation (RAG) techniques for building a robust conversational AI system. Empower insured members with the ability to instantly access and understand their policy information through intuitive Q&A interactions. Leverage open-source libraries like Hugging Face Transformers and OpenAI API.
Advanced Search: Explore and evaluate the use of semantic search techniques for internal company documents and information retrieval systems. Implement solutions like vector databases (Pinecone, Milvus, Vespa) to enhance search accuracy and user experience.
Computer Vision Applications: Design and implement cutting-edge computer vision algorithms using OpenCV, TensorFlow, and PyTorch to develop a groundbreaking dental X-ray application. Automate the identification of cavities, dental issues, and other anomalies, streamlining the claims process and improving treatment outcomes • Data Governance: Implement and uphold robust data governance policies and procedures to ensure the secure and ethical use of internal company data and imagery for machine learning initiatives while adhering to privacy regulations and industry best practices.
Data Preprocessing & Quality: Ensure data quality and integrity for machine learning models through robust data cleaning and preprocessing techniques. Prepare, wrangle, and shape data to unlock its true potential.
Model Integration & Scalability: Collaborate with cross-functional teams to integrate data science solutions into scalable, production-grade systems using open-source frameworks like Apache Spark and containerization technologies like Docker.
Cloud Infrastructure: Utilize Azure and AWS services for model training, deployment, and orchestration, while exploring cloud-native architectures for cost-efficiency and scalability.
API Development & Deployment: Develop and implement APIs using Flask, FastAPI to deploy machine learning models and integrate them into existing systems or applications.
Model Performance & Improvement: Continuously monitor model performance, conduct experiments, and iterate on algorithms using open-source evaluation tools to improve accuracy and efficiency.
Knowledge Sharing & Mentorship: Stay updated on the latest advancements in data science, natural language processing, computer vision, and generative AI research. Mentor junior team members and foster a culture of knowledge sharing and continuous learning.
Proven subscription to the company’s core values of integrity, trust and respect, innovation, stewardship, excellence, and celebration. Proven subscription to the company’s core values of integrity, trust and respect, innovation, stewardship, excellence, and celebration.

Education, Skills, Personal Attributes, and Experience Required

Candidate will have obtained a masters degree in data science, computer science, statistics, mathematics, or similar field.
Five or more years of industry experience in data science with a focus on data analytics, machine learning, and deep learning. Experience with Data Engineering and/or Dev Ops is highly desirable.
Strong proficiency in Python and libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, Numpy, Hugging Face Transformers, and OpenCV. Experience with Large Language models such as GPT, Llama, or Gemini for question answering tasks. Experience with semantic search for document retrial and RAG applications.
Experience with computer vision techniques such as object detection and object segmentation.
Experience working on cloud platforms like AWS, Azure, or GCP.
Experience with AWS services such as Lambda, Glue, SageMaker, or the Azure and GCP equivalents.
Experience with deploying APIs for machine learning models.
Experience with version control systems such as GIT.
Previous experience in the healthcare industry or insurance field is a plus.
Excellent problem-solving, analytical, and communication skills.
Commitment to organizational values and goals.

Work Conditions

General office working conditions which may require sitting for extended periods of time.

Physical Requirements

The physical requirements described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Specific vision abilities require the ability to focus distant and near objects clearly. While performing the duties of this job, the employee is regularly required to sit, talk, and hear. The employee is frequently required to use hands and arms to handle, feel and reach as well as operate a personal computer.