Data Scientist
Limelight Health
Summary
As a Data Scientist you will build and deploy data-driven solutions to support business goals. You will use your skills in data analytics, machine learning (supervised and unsupervised) and GenAI, to translate complex data into actionable insights. As a data scientist you will work closely with cross-functional team of data engineers, product owners, Devops and bridge the gap between technical implementation and business needs.
Responsibilities (Other duties may be assigned.)
- Experiment and feature engineer with data to design and build machine/deep learning models with appropriate precision, recall, F1 scores to meet the use case need
- Prompt engineer to develop new and enhance existing Gen-AI applications. (Chatbots, RAG).
- Develop and implement advanced AI agents capable of performing autonomous tasks, decision-making, and executing requirement-specific workflows.
- Document and create experiment reports on the implementation and code in a way that is clear and accessible to both technical and non-technical team members.
- Perform advanced data analysis, manipulation, and cleansing to extract actionable insights from structured and unstructured data.
- Create scalable and efficient recommendation systems that enhance user personalization and engagement.
- Effectively communicate technical solutions and findings to both technical and non-technical stakeholders.
- Design and deploy AI-driven chatbots and virtual assistants, focusing on natural language understanding and contextual relevance.
- Implement and optimize supervised and unsupervised learning models for NLP tasks, including text classification, sentiment analysis, and language generation.
- Explore, understand, and develop state-of-the-art technologies for AI agents, integrating them with broader enterprise systems.
- Collaborate with cross-functional teams to gather business requirements and deliver AI-driven solutions tailored to specific use cases.
- Automate workflows using advanced AI tools and frameworks to increase efficiency and reduce manual interventions.
- Stay informed about cutting-edge advancements in AI, machine learning, NLP, and Gen AI applications, and assess their relevance to the organization.
Education and/or experience:
At least 5 years of experience working with data sciences. Preferably with a bachelors (OR Master) degree in Computer Science, Data Science, or Artificial Intelligence.
Knowledge Skills and Abilities:
- Strong understanding of mathematics including vector algebra and probability theory for understanding and explaining machine learning (discriminative and generative) models.
- Strong expertise in data analytics, pattern recognition, machine learning, including predictive modeling and recommendation systems.
- Excellent communication & documentation skills to articulate complex ideas to diverse audiences.
- Hands-on experience with large datasets and using distributed systems for analytics and modelling.
- Advanced understanding of natural language processing (NLP) techniques and tools, including transformers like BERT, GPT, or similar models including open-source LLMs.
- Strong knowledge of cloud platforms (AWS) for deploying and scaling AI models.
- Proficiency with code versioning platforms like CodeCommit and GitHub.
Technical Skills:
- Python proficiency and hands-on experience with libraries like (Pandas, Dask, Numpy, Matplotlib, NLTK, Sklearn, Pytorch and Tensorflow).
- Experience in prompt engineering for AI models to enhance functionality and adaptability.
- Familiarity with AI agent frameworks like LangChain, OpenAI APIs, or other agent-building tools.
- Advanced skills in Relational databases [Postgres], Vector Database, querying, analytics, semantic search, and data manipulation.
- Strong problem-solving and critical-thinking skills, with the ability to handle complex technical challenges.
- Hands-on experience working with API frameworks like Flask, FastAPI, etc.
- Proficiency with code versioning platforms like CodeCommit and GitHub.
Preferred:
- Hands-on experience building and deploying conversational AI, chatbots, and virtual assistants.
- Familiarity with MLOps pipelines and CI/CD for AI/ML workflows.
- Experience with reinforcement learning or multi-agent systems.
Language Skills
- Ability to speak the English language proficiently, both verbally and in writing.
Work Environment
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Employee works primarily in a home office environment.
- The home office must be a well-defined work area, separate from normal domestic activity and complete with all essential technology including, but not limited to; separate phone, scanner, printer, computer, etc. as required in order to effectively perform their duties.
Work Requirements
- Compliance with all relevant FINEOS Global policies and procedures related to Quality, Security, Safety, Business Continuity, and Environmental systems.
- Travel and fieldwork, including international travel may be required. Therefore, employee must possess, or be able to acquire a valid passport.
- Must be legally eligible to work in the country in which you are hired.
FINEOS is an Equal Opportunity Employer. FINEOS 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.