MODULE LEAD - Quantitative Analysis

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 teams 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 datas full potentialensuring 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

Masters 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