Consultant - Patient Analytics

Chryselys; Hyderabad; Hybrid; INR 2,000,000 - 4,000,000; Full time

Job summary

Chryselys in Hyderabad seeks a Senior Pharma Analytics Lead to drive patient-level analytics, modeling, and strategic insights for pharma clients. You will design scalable data solutions, build predictive models, and deliver dashboards that support sales, marketing, and market access decisions.

The role requires strong communication, agile collaboration, and stakeholder management to align analytics with business goals and ensure governance and timely delivery.

Qualifications

• Bachelor's in statistics, data science, engineering, or related quantitative field.
• Master's/MBA preferred.
• 2+ years in pharma analytics or patient-level data; 3+ years in analytics/decision sciences.
• Experience with SQL, Python/R, and visualization tools.
• Knowledge of HCP segmentation and MMM or OCE analytics is a plus.

Responsibilities

• Lead patient journey analytics using longitudinal patient-level healthcare data to build analytical solutions for pharma clients.
• Perform treatment pattern analysis, disease progression studies, and patient segmentation to identify high-value populations.
• Translate complex datasets into clear, actionable insights for sales, marketing, and market access teams.
• Design and implement scalable data analysis using statistical modeling, machine learning, and analytics techniques.
• Build, validate, and operationalize predictive models, pipelines, and dashboards for patient identification and segmentation.
• Apply ML techniques and compare methods for fit, accuracy, and interpretability.
• Plan and deliver DS projects, guiding workstreams from framing to insight delivery.
• Lead end-to-end data analysis: querying, transforming, and visualizing insights for business audiences.
• Collaborate with business and IT to ensure governance, accuracy, and timeliness.

Skills

Strong communication

Agile / client-facing

Stakeholder engagement

Project management

HCP segmentation knowledge

Education

Bachelor's in Statistics, Data Science, Engineering, or related quantitative field

Master's/MBA preferred

Tools

Databricks

Snowflake

Delta Lake

SAP

Model N

Tableau

Power BI

MicroStrategy

Qlik

SQL

Python

R

PySpark

SAS

Job description

Core Responsibilities

Patient-Level Analytics & Insights

• Lead patient journey analytics using longitudinal patient-level healthcare data (claims, EMR, pharmacy, lab) to build robust analytical solutions for pharma clients.
• Perform treatment pattern analysis, disease progression studies, and patient segmentation to identify high-value populations and optimize targeting strategies.
• Translate complex APLD datasets into clear, actionable business insights for sales, marketing, and market access teams.

Advanced Analytics & Modeling

• Design and implement scalable, compliant data analysis solutions using statistical modeling, machine learning, and commercial analytics techniques
• Build, validate, and operationalize predictive models, pipelines, and dashboards for patient identification, HCP segmentation, and promotional optimization
• Apply and evaluate statistical/ML techniques relevant to pharma analytics (e.g., MMM, Test & Control, OCE analytics, budget optimization); compare methods for fit, accuracy, and interpretability

Solution Architecture & Delivery

• Support planning and day-to-day execution of Decision Sciences projects, owning defined workstreams and deliverables from problem framing through insight delivery
• Lead end-to-end data analysis: querying data, interpreting and transforming it, and creating insights visualized in charts/dashboards for business audiences
• Collaborate with business and IT stakeholders to align analytical approach with strategic goals and ensure data governance, accuracy, and timeliness.

Stakeholder Engagement & Influence

• Partner with cross-functional teams (commercial, digital, medical, access, NPP) to clarify objectives, scope, timelines, and resource needs; maintain project trackers and documentation
• Present recommendations that build investment, targeting, and channel strategy; communicate implications and next-best actions to senior leadership
• Drive adoption of analytics capabilities by embedding insights where decisions happen and measuring impact to scale what delivers competitive advantage

Required Skills & Experience

Education

Bachelor's in Statistics, Data Science, Engineering, or related quantitative field; Master's/MBA preferred

Experience

58 years in pharma/life sciences analytics with 2+ years in APLD or patient-level data; 3+ years in analytics/decision sciences with 2+ years in PharmaTech domain

Technical Skills

SQL (required), Python/R, PySpark; advanced Excel; Tableau/Power BI; experience with commercial analytics tools (Market Mix Modeling, Test & Control, OCE analytics)

Data Expertise

Patient-level datasets (claims, EMR, specialty pharmacy, lab); US pharma commercial data; omnichannel marketing measurement; HCP segmentation

Soft Skills

Strong communication to influence senior decision-makers; ability to work in agile, client-facing settings; stakeholder engagement and project management

Typical Tools & Platforms

• Data Sources: Claims (IQVIA, Komodo, Truven), EMR (Optum, Flatiron), Specialty Pharmacy, Lab Data, CRM (Salesforce, Veeva)
• Analytics Platforms: Databricks, Snowflake, Delta Lake, SAP, Model N
• Visualization: Tableau, Power BI, MicroStrategy, Qlik
• Programming: SQL, Python, R, PySpark, SAS