Enable job alerts via email!
Boost your interview chances
A leading company is seeking a Data Science Team Lead to direct all data science activities for multi-year studies focused on health and wellness. The role involves leading a team, conducting advanced statistical analysis, and collaborating with various stakeholders to derive meaningful insights from data.
Data Science Team Lead to direct all data science activities on several multi-year industry-sponsored studies focused on health and wellness. This individual will lead a team of data scientists in performing advanced statistical and machine learning analysis of longitudinal and cross-sectional data with a focus on making robust inferences related to health and wellness.
The MacRae Lab is seeking a dynamic and experiences Data Science Team Lead to direct all data science activities on several multi-year industry-sponsored studies focused on health and wellness. This individual will lead a team of data scientists in performing advanced statistical and machine learning analysis of longitudinal and cross-sectional data with a focus on making robust inferences related to health and wellness. Qualified candidates will have advanced formal training in computer science, including design and analysis of observational and experimental studies, causal inference, and strong statistical computing and programming skills. Comfort with a broad range of data types, including sensor and survey data is required. The candidate will work with senior & junior data scientists and report directly to senior leadership. The candidate will also work directly with the sponsor's data science teams. The team lead will be the sounding board for the entire data science operation, guiding, training, and mentoring the other staff members. There will be the opportunity for career development with respect to authorship opportunities for journal manuscripts and abstracts/posters for professional scientific meetings.
This role will be responsible for working with large scale raw sensor data. The analytical strategy will be based primarily on longitudinal analyses and machine learning techniques. Longitudinal analyses will employ mixed-effects models to understand parameter distributions over time. Machine learning algorithms like Random Forests will be used to predict clinical outcomes, emphasizing interpretable models and features of importance. Raw sensor data (and derived physiological metrics) will be processed and transformed into meaningful/analyzable features, including removal of noisy measurements and imputation of missing values when applicable. Preprocessing will be applied to each sensor and physiological measure, focusing on capturing characteristics that are most important for resilience marker identification. This position is expected to be the lead data scientist on the projects and will be responsible for independently determining appropriate pathways and setting the standard for junior staff.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
Lead data science strategy and execution across all projects, ensuring scientific rigor and reproducibility.
Assemble and explore multiple large datasets of observational data, both survey and sensor based, to define and test hypotheses related to predictors of health, disease and resilience (~25%)
Assemble and explore datasets of clinical outcome data from electronic health records (e.g., hospital readmissions, adverse events, lab values) that are potentially associated with readouts from wearable sensor data (~25%)
Lead and perform statistical analyses (including planning, programming, analysis, interpretation, visualization and writing of results) to address research questions (~25%)
Prepare and write all components of manuscripts, abstracts, and presentations at scientific meetings with assistance from Chief Data Scientist and Principal Investigator
Building machine learning predictive models using a variety of inputs derived from wearable device sensors
Mentor, guide, and train all data science staff members. This will included organizing growth opportunities such as journal clubs, poster presentations, etc...
Work with senior leadership to determine staffing needs and participate directly in the hiring and firing of data science staff.
Present work internally and to study sponsor in both scientific and non-scientific settings
Provide feedback regarding newly proposed study instruments and questionnaires
Write code using a collaborative version control system, ensuring proper documentation and periodic refactoring
Rearrange data in a format that allows for accurate use as well as possible integration and pooling across multiple data sets
Ability to incorporate clinical inferences in data analysis, specifically elements of HR, HRR, HRV, VO2 Max
Maintain department service standards as outlined in the BWH Code of Conduct
Performs other duties as required and as appropriate
QUALIFICATIONS:
SKILLS/ ABILITIES/ COMPETENCIES REQUIRED: