The opportunity
Personalized healthcare is the future. Working on Lingo, you will help build a next-generation technology that enables individuals to make decisions about how to improve energy, lose weight or enhance athletic performance. The Lingo team embodies a start-up culture and mindset with the backing of Abbott, a company with a rich history of healthcare innovation. Join us and grow your career as you help Abbott shape the future of healthcare.
You will apply your strong expertise in artificial intelligence by using machine learning to design, prototype, and build next-generation advanced analytics engines and services. You will work closely with software engineers, data architects, designers, and product owners and develop AI features, predictive models using machine learning and other advanced analytics tools to increase and optimize customer experience, revenue generation, prospect targeting, and other business outcomes.
This position works out of our Alameda, CA location in Lingo.
What you’ll do
Work within an agile team in a dynamic, fast-moving, collaborative environment and design complex analytics models and algorithms that drive analytical solutions throughout the organization
Develop data and model pipelines with tools like Azure ML SDK, Azure Data Factory, Databricks, Spark, or related technologies
Analyze large amounts of data to discover trends and patterns, and build analytics models
Ensure the highest level of data accessibility, security, and quality at all stages; create automated anomaly detection systems and monitor their performance and model drift
Effectively communicate complex ideas and results to both technical and business/executive audiences
Conduct advanced statistical and other analysis to provide actionable insights, identify trends, and measure performance
Create repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytics data products
Design, develop, and deploy AI-powered conversational experiences, including chatbots and virtual assistants leveraging Large Language Models (LLMs), retrieval-augmented generation (RAG), intent classification, grounded responses, and policy-based controls.
Qualifications
Bachelor’s degree, Advanced degree in computer science, biomedical, bioengineering, data science, or relevant, is preferred.
8+ years of relevant experience in the data science/analytics space
Strong expertise in Python as well as proficiency in writing complex SQL queries
Proficiency in using machine learning to solve clustering, classification, regression, anomaly detection, simulation, and optimization problems on large-scale data sets
Strong hands-on experience and expertise in one or more big data technologies, i.e., Hadoop, Spark, H20.ai, cloud AI platforms, containerization
Experience supporting deployment, monitoring, maintenance, and enhancement of analytics models
Experience building and deploying AI-powered conversational solutions, including intent classification, retrieval-augmented generation (RAG), grounded response generation, policy and guardrail implementation, validation methodologies, and evaluation frameworks for production use cases.
Up to date on industry trends within the analytics space from a data acquisition processing, engineering, and management perspective
High level of curiosity, creativity, and problem-solving capabilities
- The base pay for this position is
- $114,000.00 – $228,000.00
- In specific locations, the pay range may vary from the range posted.
JOB FAMILY
Product Development
DIVISION
LNGO Lingo
LOCATION
United States > Alameda : 2901 Harbor Bay Parkway
ADDITIONAL LOCATIONS
WORK SHIFT
Standard
TRAVEL
No
MEDICAL SURVEILLANCE
No
SIGNIFICANT WORK ACTIVITIES
Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans.
EEO is the Law link - English: http://webstorage.abbott.com/common/External/EEO_English.pdf
EEO is the Law link - Espanol: http://webstorage.abbott.com/common/External/EEO_Spanish.pdf