Role- Senior Data Analyst/Scientist
Locations- Remote
Durations- 6+ Months
Exp Level- 10+ years
USC/GC/H4
JOB SUMMARY
The Technology Solutions business unit is the client's Health accelerator for life sciences technology and innovation. Our work supports getting meaningful new medicines to patients faster with greater positive impact. Technology Solutions homegrown products and applications, commercial off-the-shelf, and software-as-a-service products ensure all employees work in a secure environment with clean data and deliver insights as part of our integrated strategy for customers.
As a Senior Data Scientist, you will play a critical role in designing and implementing analytical frameworks, developing predictive and prescriptive models, and translating data into actionable recommendations. You will work with diverse datasets and collaborate with cross-functional teams to influence strategic decisions through the application of data science methodologies. In this role, you will also engage directly with clients, translating complex analytical concepts into clear business insights and ensuring that data-driven solutions align with their strategic objectives.
JOB RESPONSIBILITIES
Lead the design and execution of advanced machine learning and causal inference models to measure and optimize omnichannel engagement strategies.
Exercise independent judgment in methods, techniques, and evaluation criteria on data science projects, overseeing the end-to-end process from problem definition to model implementation.
Work with large-scale healthcare datasets, including claims data, prescription data, digital engagement logs, and survey data, to derive insights on HCP behavior.
Partner with commercial, marketing, and business development teams to translate data insights into strategic recommendations that enhance customer engagement.
Act as a key data science representative in client engagements, effectively communicating insights, methodologies, and recommendations to both technical and non-technical stakeholders.
Have broad analytics experience or innovative knowledge and use skills to contribute to achieving client objectives in creative and effective ways.
Foster innovation by exploring and integrating emerging technologies and methodologies.
QUALIFICATION REQUIREMENTS
Master's degree or equivalent experience in Data Science, Computer Science, Mathematics, Statistics, or a related field. PhD is preferred.
Proficiency with programming languages like Python, R, and SQL.
Experience applying causal inference techniques (e.g., causal impact analysis, uplift modeling, DoWhy) to marketing and engagement analytics.
Strong background in predictive modeling, classification, segmentation, and optimization.
Familiarity with healthcare and commercial biopharma data sources such as claims data, HCP interaction logs, and prescription data.
Experience engaging with clients and strong ability to bridge the gap between technical and business audiences.
Ability to translate complex data science concepts into strategic business insights for non-technical stakeholders.
Experience deploying models in cloud-based environments (AWS, Azure, or GCP) is a plus.
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