About the role
As a Quantitative Scientist working on feasibilities in Analytic Solutions , you
play a key role in generating initial feasibility assessments for life science companies that want
to utilize data for clinical development and commercial impact. The Data & Science team?s work
directly improves quality of care for patients, and your contributions will help us explore the
data to ensure fit-for-purpose alignment with the use cases from our clients to effectively
harness the data?s full potential?ensuring clinical insights translate into better health outcomes.
What You Get To Do Lead execution of initial queries and feasibility requests surfaced by customers
Be at the forefront of understanding what life science companies are interesting in
leveraging real-world data for
Inform in a data-driven manner whether questions are a good match and well aligned
with customer solutions
Present and communicate findings to internal partners, supporting decision-making and
innovation
Contribute to a culture of learning and scientific rigor, continuously improving
methodological standards
Skills and Experience that Will Help You Succeed ?
Proven expertise coding and analyzing healthcare datasets to generate metrics based on
real-world data
Demonstrated ability to execute implementation requirements that include subsetting a
large clinical database to a select set of patients that meet a number of criteria
Ability to collaborate cross-functionally with teams (e.g., Commercial, Product, Medical,
Engineering, etc.) to translate clinical investigation questions into programming logic
Essential Requirements - Overall experience 5+ years Master?s or Doctorate in Engineering, Computer Science, Math, Statistics, or related
quantitative field, or equivalent hands-on experience
3+ years of direct experience with healthcare datasets (EHR, outcomes, messy/complex
data)
Experience querying large-scale relational databases
Expertise in Python, PySpark, cloud environments (AWS), Databricks, and Git-based
workflows
Experience with cross-functional teams and translation requests into aggregate metrics Quantitative Scientist - Analytical Engineer We are seeking a highly analytical and data-driven Sr. Quantitative Scientist - Analytical Engineer to develop advanced statistical models, machine learning algorithms, and Data Modelling to address complex business challenges. The ideal candidate will possess strong expertise in mathematics, statistics and programming, with the ability to translate large datasets into actionable insights.
Key Responsibilities
Develop, validate, and optimize quantitative models for predictive analytics and decision-making.
Apply statistical techniques, machine learning algorithms, and mathematical modeling to solve complex problems.
Analyze large structured and unstructured datasets to identify trends, patterns, and opportunities.
Design and implement data-driven solutions to improve business performance and operational efficiency.
Collaborate with cross-functional teams including Data Science, Engineering, Product, and Business stakeholders.
Perform hypothesis testing, experimentation, and model evaluation.
Develop scalable analytical frameworks and automation tools.
Communicate findings and recommendations to technical and non-technical stakeholders.
Ensure model governance, explainability, and compliance with organizational standards.
Quantitative Analysis, Data Modelling, Data Quality, Statistical Modelling
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