Consultant - APLD

Chryselys; Hyderabad; On-site; INR 900,000 - 1,200,000; Full time

Job summary

Chryselys seeks a data analytics professional to lead patient-level analytics for pharma clients, translating complex datasets into actionable business insights. The role emphasizes modeling, dashboards, and stakeholder communication across commercial, medical, and access teams.

You will apply statistical and ML methods to optimize targeting, measurement, and promotional strategies while collaborating with cross-functional teams in an agile, client-facing setting.

Qualifications

• Bachelor's degree in Statistics, Data Science, Engineering or related quantitative field.
• Master's/MBA preferred.
• 5+ years in pharma/life sciences analytics with 2+ years in patient-level data or APLD.
• 3+ years in analytics/decision sciences with PharmaTech domain experience.

Responsibilities

• Lead patient journey analytics using longitudinal healthcare data to build analytical solutions for pharma clients.
• Perform treatment pattern analysis, disease progression studies, and patient segmentation to optimize targeting.
• Translate APLD datasets into clear insights for sales, marketing, and market access teams.
• Design scalable data analysis solutions using statistics and ML techniques.
• Build and operationalize predictive models, dashboards, and pipelines for patient identification and HCP segmentation.

Skills

Strong communication

Stakeholder management

Agile working

Client-facing experience

Education

Bachelor's in Statistics/Data Science/Engineering

Master's/MBA preferred

Tools

SQL

Python

PySpark

R

Excel

Tableau

Power BI

Databricks

Snowflake

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