AI/ML Engineers code and develop software that deploys ML models and algorithms into production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR).Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. May adapt machine learning to areas such as artificial intelligence, robotics and other products that allow users to have an interactive experience. Work with large scale computing frameworks, data analysis systems. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory and machine learning using code for tool building, statistical analysis, using both general purpose software and statistical languages.

Primary Responsibilities:

• Be a hands-on leader of a team of AI/ML researchers in the Optum AI team and solve real-world problems in the Healthcare domain using cutting-edge capabilities and emerging technologies

• Leverage UHG’s big data analytics infrastructure, as well as cloud environments, comprising Hadoop, R, Python, HIVE, SPARK to tackle previously unsolved problems across Clinical Natural Language Processing, Risk and Quality, Customer Engagement and Experience, Cyber Security etc.

• Deliver advanced Machine Learning capabilities in a meaningful manner through successful proof-of-concept solutions, and later on smoothly transition the proof-of-concept into production, partnering with delivery Data Science and Technology teams. E.g. Build and demonstrate a prototype

• Reinforcement Learning application in the Healthcare space

• Conduct evaluations and assessments of new tools and technologies to ensure that the team stays at the frontier of Artificial Intelligence & Machine

• Learning. E.g., Evaluate application of Knowledge Graphs on life sciences data

• Assist Data Science delivery teams working on advanced projects as an expert when assistance is required. E.g., Build the Natural Language

• Processing module for interpreting electronic Medical Records

• Participate in the process to mature the EDA Data Science practice in terms of developing best practices related to Data Science and Machine

• Learning; identifying appropriate training to keep the community upskilled on latest tools and methodologies; and lead expert groups for one or more specialized topics

• Submit invention disclosures to the UHG Invention Program and ensure filing of patents

• Write White Papers and Blogs to evangelize ideas and drive adoption with the broader enterprise

• Present in leading academic and industry conferences to showcase expertise and solutions, and publish Research Papers

• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Graduate degree from a renowned institute in: Engineering/Statistics/Economics/Computer Science/ Mathematics (with a solid quantitative background)

• Experienced researcher with 10+ years of experience in developing and deploying Machine Learning (ML) solutions to generate business value

• Minimum of 4 years of mentoring, and grooming a small team of Data Scientists / ML Engineers

• Worked in Healthcare and have prior understanding of the kind of data, systems and problems involved in Healthcare

• Worked hands-on using pre-trained models leveraging Transfer Learning, as well as using frameworks / libraries for NLP (e.g. Hugging Face, spaCy etc.) and CV (e.g. OpenCV)

• Demonstrated hands on experience in using algorithm libraries / frameworks like PyTorch, TensorFlow and H2O

• Demonstrated hands on experience in working with Big Data technologies such as SPARK

• Worked hands-on on the cloud and have familiarity with cloud-based AI/ML services

• Solid theoretical and practical knowledge of some or most econometric/statistical methods like Linear Regression, Logistic regression, Generalized Linear Model, Survival Analysis, Sampling Techniques, Time Series Analysis, CART, CHAID, Clustering, Discriminant Analysis, Principal Component Analysis, Factor Analysis, Multidimensional Scaling etc.

• Solid theoretical and practical knowledge of some or most Machine Learning techniques like Random Forest, Support Vector Machine, Gradient Boosting Machine, XGBoost etc.

• Solid theoretical and practical knowledge of some or most Deep Learning techniques across Recurrent Neural Networks, Convolutional Neural Networks etc. and Transformer Architectures as applied in the domains of Natural Language Processing (NLP) and / or Computer Vision (CV)Consistent track record of building and successfully deploying Machine Learning solutions with demonstrable value to the organization

• Solid to Expert level programming ability Python

• Proven ability to possess solid technical writing skills and must have published research papers in leading academic journals on topics related to Artificial Intelligence & Machine Learning

• Proven ability to possess good presentation and public speaking skills; ability to organize and present information to audiences with disparate levels of technical understanding

• Proven ability to work well in a matrix organization and possess solid collaboration skills as well as the ability to build partnerships

• Proven ability to work well under pressure in a fast-paced environment

• Proven excellent consulting skills, including the ability to engage with and present to CXO leaders as well as stakeholders with minimum to high analytics exposure across various departments in an organization.

• Proven good conflict management and prioritization skills

• Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes and recommend solution

• Proven professional, service oriented, proactive and flexible

Preferred Qualifications:

• Post-graduate degree

• Experience in ML R&D with demonstrable impact

• Exposure to U.S. Healthcare

• Knowledge of Java and / or R

• Knowledge of Azure See Less