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About Hopscotch HealthHopscotch Health is a technology-driven healthcare startup focused on building the future of healthcare, by bringing together the best practices from data science, artificial intelligence, and behavior science. We work with our partners from hospitals, clinics, and social organizations to create comprehensive programs for chronic disease management. What sets us apart is that we’re data smart - our technology is highly adaptable to the most pressing healthcare problems. Through our partnerships with and talent from organizations including Carnegie Mellon University, Tata Institute of Social Sciences, and Asian Cancer Institute, we’re making the tools to monitor and improve health simple, intuitive, and human. Join us in building the healthcare system of the future! Our Values: We believe that everybody should be able to afford quality healthcare access, that any healthcare system should account for not just medicine but all the determinants of health and that technology can help us get there faster. To read more about the potential of artificial intelligence and behavioral science to tackle large healthcare challenges, click here. Our North Star goal is to establish a roadmap for the implementation of Universal Healthcare. To target some of the biggest challenges head-ons, we’re building programs tackling tobacco cessation and diabetes management in resource-constrained populations. To read more about the chronic disease epidemic in India, click here. About the role: We are looking for a data science expert who has 2 to 3 years of hands-on experience in Python with broad experience in machine learning and cloud AI. We’re looking for a dynamic self-starter given the varied nature of remote work and the agility of the startup environment. Key responsibilities: Lead and manage a team of data entry personnel and junior data analysts Create and maintain automated systems for ensuring data quality Maintain ETL and machine learning pipelines Build and iterate on reproducible machine learning experiments Interface with the backend, front office, and algorithm teams build data delivery pipelines Does this sound like you? Must-haves: Strong grasp of core principles with 2 to 3 years of hands-on experience with Python Conversant with NoSQL and data streams Prior experience in ML - predictive modeling, tensor flow, NLP Prior experience with AWS or another cloud platform
We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations , clinical named entity recognition and information extraction from clinical notes. This is a role for highly technical machine learning & data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals. You will be responsible for setting an agenda to develop and ship machine learning models that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company, and help build a foundation of tools and practices used by quantitative staff across the company. What you will achieve: Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space Partner with the executive team and other business leaders to deliver cross-functional research work and models Required Skills: Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience Knowledge of deep learning & NLP Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets. Experience with GPU computing is a plus. Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company. Expert-level experience with a wide range of quantitative methods that can be applied to business problems. Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization. Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders. Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling Qualifications Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization Expert-level experience with machine learning that can be applied to business problems Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application) 5+ years of industry experience in data science and machine learning, preferably at a software product company 3+ years of experience managing data science teams, incl. managing/grooming managers beneath you 3+ years of experience partnering with executive staff on data topics
