Director, Data Science & ResearchApply
SN LABS, a subsidiary of Sleep Number Corporation, is a fast moving, highly technical team of people with the ambitious goal of bringing people better health and well-being through the best possible sleep experience. We combine our established expertise in creating comfortable, adjustable beds with the latest in sleep science, cutting-edge sensor technology, and data processing algorithms. SN LABS is the pioneer of biometric sensor solutions and sleep monitoring technologies and owns the most comprehensive sleep data base in the market.
As a Director on our Data Science & Research team, you will play a key role in strategically leading software solutions leveraging bio signal data to support our innovative strategy to maximize customer benefit in the form of improved sleep and sleep data-based insights. Specifically, you will be involved in working with the executive leadership team and cross functional leaderships teams to deliver sleep and health capabilities with an emphasis on scale, performance, and interpretability.
- Leading Research & Development efforts for the next generation of products, features, services and technologies
- Research and development of digital signal processing and machine learning methods for noninvasive sleep & health monitoring
- Managing new product R&D projects starting from concept to feasibility studies, and to proof-of-concept prototypes, and shepherding their development as commercial products
- Applied algorithm development for health and wellness
- Lead the design and development of advanced machine learning methods for big sleep data
- Collaborating cross-functionally to bring research ideas from concept to product development, integration and commercialization
- Providing key technical input and implementation strategies to drive the company’s short- and long-term objectives
- Plans and directs all aspects of research activities and projects within Algorithm Development. Ensures all research projects, initiatives, and processes are in conformance with organization's established policies and objectives. Utilizes best practice research methods and provides expert technical guidance for research initiatives. Incorporates strategy, investigations, and trials that result in new and remarkable features for the
- R&D team building and training
- Lead development of distributed applications, platform infrastructure, and interface to solve large-scale processing problems.
- Work with embedded and cloud-based software engineering teams to scale and operationalize prototyped concepts and to ensure successful implementation and deployment of algorithms.
- Stay abreast of latest data science developments and determine if/how these can best be incorporated in our designs.
- Lead various stake holders (e.g., product, engineering team, and external ML partners) to develop analytics and ML/AI solution roadmap and identify key requirements and drive the validation of requirements in the market by working with early customers.
- Lead the cross functional team to develop, implement, and monitoring the production-scale analytics products (such as standard dashboards) and ML/AI algorithms on the platform Provide design input specifications, requirements, and guidance to data and software engineering team for building robust data pipeline, and deploying and optimizing the analytics products and ML/AI algorithms
- Lead analytics initiatives to support customer project deliveries and drive insights for the customers from the data captured on the platform
- Become a thought-leader, and stay up-to-date in the field of machine learning, AI, and deep learning
- Support business development and marketing process, and present ML/AL methodology and business value effectively to customers and external partners
- Collaborate with engineering and research teams to improve algorithms and to support advanced features.
- Work closely with management and cross functional teams to ensure successful implementation and deployment of algorithms.
- BS/MS degree in biomedical engineering, computer engineering, data science, computer science or similar fields
- PhD is a plus
- 10+ years of experience / with at least 5 years’ experience in a senior leadership role
- Demonstrated experience incubating new technology leading research scientists, software developers, and technical professionals from product conception to implementation.
- Experience delivering bio-science products targeted towards end consumers
- Previous experience leading a globally distributed bio/data science engineering team
- Experience with Agile and waterfall methodology
- Experience successfully leading many significant technical projects to completion
- Strong track record of delivering complex, high value deliverables through organizational change, development, market analysis, product and program management
- Proven success in managing/leading team of engineers and research scientists
- Proven ability to attract, build, develop, inspire and motivate technical teams in a fast-paced engineering organization across multiple locations
- Experience working in a fast-paced, high-tech software development environment and comfortable navigating conflicting priorities and ambiguous problems
- Exceptional communication skills and an ability to connect people with different points of view and with varying levels of experience
- Technical depth in: Bio-Science Technology Product Development, User Experience, Internet of things (IOT), AWS Cloud Computing, location-based services, hardware, software and digital signal processing development, UI/ UX and quality assurance experience
- Understanding of advanced Biomedical Signal Processing and Machine Learning: DNN, Signal Processing
- Cardio-Respiratory Patient Monitoring: Filtering, Delineation, Segmentation, Compression, Feature
- Extraction, Classification, Cardiac Risk Stratification, Myocardial Infarction Detection, T-wave Alternans
- Analysis, ECG Modeling, Heart Rate Variability Analysis, ECG-Derived Respiration Rate Estimation
- Cardiac Rhythm Management: Cardiac Electrophysiology, Electrocardiography (body surface and intracardiac electrograms from implantable devices), Diagnostic and Therapeutic Cardiac Technologies
- Data Analysis: Algorithm Development, Real-Time Data Processing, Learning and Inference, Statistical and Probabilistic Analysis, Validation Techniques
- Programs: Matlab, LabView, Stata, Python, Tensorflow
- Strong background and experience in building products based on AI/data science
- Strong background in signal processing theory and application.
- Pragmatic, product-oriented approach
- Ability to mentor engineers
- Ability to recruit talented engineers
- Ability to drive complex projects and deliver products for consumer and health sectors
- Publications or patent applications is a plus
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“We have the freedom of a start-up to explore new technology and methods, backed by a strong company like Sleep Number.”Abhishek, Director of Analytics