Director of Data Science
San Jose, CA
Do you want to be part of the Digital Health revolution that’s changing the face of healthcare? Do you enjoy working with high performers in a fast-paced and agile environment? Then come join us at BrightInsight. Backed by top tech and healthcare VC's, BrightInsight provides the leading global regulated digital health platform for biopharma and medtech. We are a start-up comprised of highly experienced and driven individuals from medtech and biopharma with a mission of making digital health innovation easy for our customers. Our medical-grade IoT platform is built under a Quality Management System to support and optimize regulated drugs, devices and software through integrated data and actionable insights. Since launching the BrightInsight Platform in 2018 we have secured the world's top biopharma companies as customers including Novo Nordisk and Roche, were selected as the “Best IoT Healthcare Platform” in the 2019 MedTech Breakthrough Awards, included in CIOReview Magazine’s “20 Most Promising Biotech Solution Providers 2019 and were awarded “2018 Google Cloud Partner of the Year for Healthcare and Life Sciences” by the world’s leading tech titan. If you are passionate about transforming healthcare and want to make a meaningful impact on patient’s lives, then come be a part of the leading Digital Health start-up in Silicon Valley.
Director of Data Science will be responsible to drive Brightinsight’s advanced analytics and machine learning (ML)/AI strategy, and solution roadmap, and lead the development and deployment of analytics and ML/AI solutions on the Brightinsight platform.
We are looking for someone who thrives in a start-up environment and demonstrates:
- Intensely collaborative
- Passionately focused on the customer
- Disciplined executor of responsibilities
- Tenacious commitment to continuous improvement
- Relentless drive to win
- Intense curiosity on technology
- Flexibility and willingness to learn
Here is a glimpse of what you’ll do…
- Lead various stake holders (eg. 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.
- Build advanced analytics and ML/AI prototype and POC for customer demo and providing insights on full implementation requirements
- 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
Here is some of what you’ll need…
- MS or Ph.D (preferred) degree in a quantitative discipline (e.g., statistics, operations research, bioinformatics, economics, computer science, mathematics, physics, etc.)
- Minimum 5 years of relevant work experience, including expertise in dashboard and reporting, recommendation systems, personalization, collaborative filtering, predictive modeling, NLP, etc.
- Proven track record of analyzing large-scale complex data sets, building and deploying machine learning algorithms from prototyping to production
- Deep understanding of machine learning and deep learning methods with their underlying theory and math
- Hands-on experience with machine learning and deep learning frameworks and tools, such as TensorFlow, Keras, Spark ML, Torch etc.
- Proficient in at least one of the key ML programming language, such as Python, Java, Scala, or R.
- Experience with distributed systems such as Hadoop/MapReduce, Spark, streaming data processing, cloud PaaS platform (such as AWS, GCP or Azure), is a plus
- Experience in building ML models using IOT devices data is a plus
- Excellent written and verbal communication and presentation skills are required
- Healthcare industry experiences is a strong plus