Remote, Direct-Hire opportunity with a leading medical technology company in the health economics and outcomes research (HEOR) discipline
This individual will conduct analyses and research to produce results and identify solutions to provide support for project analytics. This role will serve as a subject matter expert in machine learning for both clients and internal stakeholders. The position will assist communication efforts lead by the project manager or other staff to show the value proposition and evidence to achieve maximal commercial success of products throughout their life cycle. This will include providing outputs to be used in various deliverables and helping to interpret outcomes for clients and other stakeholders. The Senior Data Scientist should have a deep understanding of RWE/HEOR studies (which will also include payer analytics tools such as input to RCT & RWE design & analyses, meta-analyses, predictive analytics, statistical comparisons, and indirect and mixed treatment comparisons) as well as the application of machine learning techniques and their application to healthcare data to gain new insights for our customers.
Purpose of Role
The Senior Data Scientist, Machine Learning will be responsible for supporting innovative research strategies and activities and to produce scientific evidence and support publications for our pharmaceutical clients.
Main Responsibilities / Critical tasks
- Provide leadership and guidance on all analytic aspects of project work
- Provide support to lead scientists throughout the project life cycle
- Extensive knowledge of various healthcare datasets and data types including claims, EMR, etc.
- Provide mentoring and training to junior level staff
- Proactively address complex analytical issues. Handle unforeseen circumstances and actively monitor and apply new analytical techniques
- Provide support drafting materials for project related content as well as internal research
- Collaborate with medical writers and project managers to provide RWE input on manuscripts and other similar deliverables and review RWE -related publications for technical accuracy and quality of technical literature review
- Responsible for quality control of all analytic work including deliverables related to the project
- Interact with cross-functional team members at a project level.
- Ability to work in a fast-paced and accountable environment
- Serve as analytics lead on projects and produce or provide guidance on all analytic deliverables
- Perform ad hoc analyses as needed
- Provide guidance to the project lead, research analysts and clients on analytic approaches that are appropriate to project work as needed
- Ensure quality control is maintained and that project materials such as programming code, analytic files and SAS logs are properly archived
- Training and mentorship for junior level staff and evaluation of staff performance
Skills & Knowledge
- Demonstrated ability to work in different types of datasets, analyze data tied to study designs, and interpret results in the context of peer reviewed publications
- Assess data quality and completeness. Create queries for calculating metrics and benchmarks.
- Excellent understanding of machine learning techniques and algorithms including clustering, decision trees, Bayesian techniques, random forests, neural networks, etc.
- Experience with common data science toolkits and libraries, such as scikit-learn, Pandas, NumPy, SciPy, Matlab, etc.
- At least 2 years’ experience using R, R Shiny and Python for machine learning projects
- Strong knowledge of SQL and data manipulation techniques
- At least 2 years’ experience of machine learning experience using real-world data
- Great verbal and written skills
- Provide mentorship and training to the analytics team and serve as a thought leader on machine learning
- Knowledge of application of deep learning to real-world data is a plus
- Serve as the internal primary point of contact for analytic requests with a focus on machine learning and other advanced analytic techniques
- Work independently with minimal oversite and works to adhere to timelines as defined by the internal teams
- Provide excellent customer service when delivering work on projects
- Ability to communicate with stakeholders both internally and externally
- Strong organizational skills
- Expert knowledge of healthcare data and methods of data manipulation and analysis
- Expert knowledge of machine learning techniques
- Ability to work quickly and accurately for all assigned tasks
Experience, Education & Certifications Preferred
- Master or PhD degree in Engineering, Neuroscience, Bioinformatics, or other quantitative fields with at least 4 years of experience in the healthcare industry
- Strong analysis and programming experience including expert level skill in manipulating and analyzing large datasets
- Expert knowledge of SQL, R, R Shiny or Python
- Expert level experience with multiple healthcare data sources
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