Principal Data Scientist / Applied Machine Learning Engineer

Role Specification:

• 5+ years of professional experience in Data Science, 3+ years in Healthcare preferred
• Postgraduate qualification in Computer Science, Biostatistics, or other Quantitative Field from top school (PhD Preferred)
• Hands-on experience on writing production-level machine learning code
• Exposure to standard ML tooling – Python, R, and TensorFlow/Torch libraries
• Excellent communication skills
• Excellent critical thinking and problem-solving skills
• High motivation, good work ethic and maturity

Role Description

• Work closely with VP of Data Science and Sales Team to map, execute and track technical AI/ML engagements with large clients in Healthcare, covering Payer, Life Sciences, Medical Technologies, and Provider markets
• Work in a high growth environment, with the goal of significantly augmenting the capabilities of the data science team, and the implementation of valuable technologies for our partners
• Lead a team or teams of US based / offshore based Data Scientists building ML solutions end-to-end
• High visibility role, interacts with execs from major players in healthcare industry

Job Responsibilities

• Establish project scope and roadmap, including data strategy, needed to develop production-level predictive pipelines that solve large scale problems for clients in the space
• Help develop, implement and document rigorous methodology to plan, track and improve accuracy and relevance of models
• Lead internal communication with stakeholders, and ensure delivery of the project per commitment
• Collaborate with clients and other stakeholders to effectively integrate and communicate findings and use cases
• Provide guidance and project management support to the Associates on the team
• Experience building predictive models allows you to clearly determine team size and scope work needed to accomplish business goals 
• Knowledge of databases, data modeling, and data harmonization a must
• Evaluate emerging technologies and alternative datasets that may contribute value to our existing platforms
• Contribute to the thought leadership of the company by publishing ML research and participating in relevant conferences in the space
• Healthcare data familiarity, especially around claims and clinical data, is highly desirable

 CitiusTech’s data science approach is based on 3 focus areas:

• Data Science Consulting - Creation of an end-to-end AI / ML roadmap for healthcare organizations, including use cases and end-state visuals
• Model Development - Data pre-processing, data quality improvement and data mining for the development of custom AI / ML models
• Model Operationalization - Validation, deployment and monitoring of selected data science models, to generate actionable insights

About CitiusTech:

CitiusTech is a specialist provider of healthcare technology services and solutions to healthcare technology companies, providers, payers and life sciences organizations. With over 3000 professionals worldwide, CitiusTech enables healthcare organizations to drive clinical value chain excellence, across integration & interoperability, data management (EDW, Big Data), performance management (BI / analytics), predictive analytics & data science, and digital engagement (mobile, IoT). CitiusTech helps customers accelerate innovation in healthcare through specialized solutions, healthcare technology platforms, proficiencies and accelerators. Armed with cutting-edge technology & expertise, world-class service quality and a global resource base, CitiusTech consistently delivers best-in-class solutions along with an unmatched cost advantage to healthcare organizations worldwide.
CitiusTech has been recognized as a great place to work by the Great Place to Work Institute® for seven consecutive years (2012 to 2018). CitiusTech has also been listed in the 2018 Healthcare Informatics (HCI) 100, placing it among the top 100 healthcare technology companies in the US, for the third consecutive year. CitiusTech has also been closely associated with key industry organizations, such as HIMSS, HL7, CHIME Foundation and AHIP.