Senior Data Scientist

TechStarsGroup; Boston (MA); On-site; USD 100,000 - 130,000; Full time

Job summary

A leading analytics firm in Boston seeks a Senior Data Scientist to lead data science projects focused on digital biomarkers. This role requires a Master’s or PhD in a related field and at least 3 years of experience. Candidates must be proficient in Python, statistical analysis, and machine learning, with the ability to communicate findings effectively to diverse audiences. Experience with cloud platforms like AWS is preferred, alongside a strong passion for research and innovation.

Qualifications

• 3+ years of experience in data science, applied statistics, or machine learning.
• Proficient in Python, building Python libraries and models.
• Excellent communication skills for non-technical audiences.

Responsibilities

• Lead data science projects for digital biomarker discovery.
• Develop and implement code for digital biomarker models.
• Create ML/statistical models to predict patient behavior.

Skills

Python programming

Statistical analysis

Machine learning

Data visualization

Communication skills

Education

Masters degree, PhD in relevant field

Tools

AWS

Google Cloud Platform

ScikitLearn

R

Python Libraries

ETL processes

SQL

Job description

The Senior Data Scientist will play a pivotal role in providing programming, advanced statistical, and machine learning expertise to our Clinical Data Science team. This position is instrumental in supporting research initiatives focused on digital biomarkers and predictive model development within our innovative technology platform. The selected candidate will collaborate extensively with our dynamic team to fulfill analysis requirements as per our clients' needs. Responsibilities include leading data science projects related to digital biomarker discovery and patient behavior prediction. This encompasses exploratory data analysis, statistical analysis, development of inference models, creation of data visualizations, and ensuring data quality.

Essential Functions/Responsibilities:

• Develop and implement high-quality code for digital biomarker analysis and inference models as application programming interfaces.
• Conduct exploratory data analysis, statistical testing, and develop inference models to measure and validate novel digital biomarkers related to disease and behavior.
• Create machine learning and statistical models to predict patient behavior, utilizing complex, high-dimensional data.
• Engage in the assessment and implementation of computational and predictive analytics strategies to tackle research questions.
• Play a key role in defining the experimental design and research scope, including data requirements, methodology, analysis, and validation strategies.
• Independently manage experimental plans, analyze results, and report findings to leadership.
• Produce data visualizations for a variety of data types, including complex digital biomarker data and model performance metrics.
• Establish data quality metrics and conduct thorough data quality assessments.
• Work closely with the applications research team to translate digital biomarkers and models into practical product applications.
• Design and oversee continuous validation processes for systems incorporating digital biomarkers and predictive models.
• Mentor junior staff and supervise student interns.
• Communicate results to a broad audience, including clinical professionals, technical experts, and non-specialists.
• Oversee client project portfolios, ensuring clear and effective communication across multiple initiatives.
• Contribute to scientific publications, author abstracts, and present findings at professional gatherings.

Required Education & Training:

• Masters degree, PhD, or equivalent in data science, machine learning, statistics, mathematics, informatics, or a related field.
• At least 3 years of experience in complex data science, applied statistics, or machine learning projects.
• Proficiency in Python for model development, including experience building Python libraries.
• Familiarity with cloud computing environments such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).
• Skilled in developing and validating machine learning models with standard algorithms (e.g., random forest, logistic regression, support vector machines).
• Experience with statistical analysis and machine learning libraries (e.g., ScikitLearn, R).
• Knowledge of statistical analysis methods.
• Proficiency in ETL processes and SQL for data transformation.
• Excellent communication skills, capable of explaining technical concepts to non-technical audiences.
• Experience in scientific and technical writing.
• A strong passion for science, research, and innovation in a team-based setting.

Preferred Qualifications:

• Experience with deep learning libraries such as PyTorch or TensorFlow is highly desirable.