Lead Data Scientist - Deep Learning
The Lead Data Scientist uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Lead Data Scientist works on problems of diverse scope and complexity ranging from moderate to substantial. Subsequently, the Lead Data Scientist have strong prioritization skills, while being dynamic and agile. The Lead Data Scientist for this position would be applying Deep Learning to address complex business problems in an actionable manner. The Lead Data Scientist must also be able to communicate complex quantitative analyses in a clear, precise, and actionable manner to management and executive level audiences while being able to build relationships with their partners. The Lead Data Scientist must be proactive and work with a sense of urgency.
Humana’s Inc is seeking a Lead Data Scientist, focusing on Deep Learning. You will develop, maintain, and collect structured and unstructured data sets for analysis and reporting. Creates reports, projections, models, and presentations to support business strategy and tactics. Advises Executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action
We will be building state of the art AI solutions in healthcare. You would be part of an exceptional multidisciplinary team, focused on deep learning, recommender systems, reinforcement learning, speech recognition, and image processing. Great opportunity to touch on different aspects of AI, share and learn from the team.
Our dream is to bring personalized care and health insurance into reality.
This role will be based in Boston at Humana's new office - Studio H, located at 281 Summer Street in the Seaport District.
At Humana Studio H, we offer the expansive data and technology architecture needed to get things done. We’re harnessing the power and potential of predictive modeling, artificial intelligence and machine learning to revolutionize—and forever impact—the way healthcare is delivered.
Master's degree in a quantitative discipline, such as Computer Science, Mathematics or Statistics and/or related field
4+ years technical experience
2+ years project leadership experience
A very strong machine learning background with deep structured learning/hierarchical learning and statistical modeling techniques
Obtaining data from multiple, disparate data sources including structured, semi-structured and unstructured data.
Experience with Deep Learning (ANN, CNN, RNN, Auto-encoders, GAN, etc. )
Good understanding of standard NLP techniques
Deep knowledge and experience working with standard speech recognition toolkits
Experienced in recommender systems
Demonstrated experience in image processing, computer vision, image segmentation, pattern matching,
Experience with cloud-based ecosystems (GCP, AWS, Azure)
Successful demonstrated experience in working on problems of diverse scope and complexity ranging from moderate to substantial in a collaborative fashion alongside other individuals or teams.
Experience in creating reports, projections, models, and presentations to support business.
Specifically, has experience with Deep Learning models, AI development, agile software launching, Tensorflow experience, and/or working with data integration developers to assess data quality and define data processing business rules for cleansing, aggregation, enhancement, supporting analysis and predictive modelling activities.
Ability to exercise independent judgment and decision making on complex issues regarding job duties and related tasks
Ability to works under minimal supervision, using independent judgment
Presenting complex analysis results tailored to different audiences (e.g. technical, manager, executive) in a highly consumable and actionable form including the use of data visualizations
Experience working with data from wearables and Internet of Things (IoT)
Experience deploying ML and DL with wearables, apps, IoT, etc.
Experience with deploying model pipelines across various technologies, such as Kubernetes or Docker.
Interested in coaching and mentoring junior talent to grow next generation of Data Scientists
Experience with Natural Language Processing, Keras, and/ or H2O
Experience working in Agile environments (i.e. Jira)