ICON Plc Hiring Statistical Programmer | Bangalore

ICON Plc is hiring an Associate Statistical Programmer (Reference: JR163286) for its clinical analytics centre in Bangalore. This opening is tailored for freshers and graduates with degrees in Statistics, Mathematics, Computer Science, Biotechnology, or allied data domains who wish to build a high-impact career in clinical trial data analysis, SAS programming, and biostatistics.

Job Overview

ICON Plc is one of the world's premier healthcare intelligence and clinical research organizations. Partnering with top biotechnology and pharmaceutical corporations, ICON delivers end-to-end clinical trials that bring life-saving drugs and therapies to market safely.

As an Associate Statistical Programmer, you will work within the Functional Service Provision (FSP) Strategic Solutions team. You will write SAS programs and statistical scripts to validate clinical trial datasets, create standardized analysis data models (CDISC SDTM and ADaM), and generate summary tables, listings, and figures (TLFs) submitted to regulatory agencies such as the US FDA and European EMA. If you are preparing your application, our fresher resume tips and off campus drives guide offer valuable advice.

Eligibility Criteria

To qualify for the Associate Statistical Programmer position at ICON, applicants should possess:

• Educational Qualification: Master's or Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, Biotechnology, Pharmacy, or related quantitative sciences.
• Experience Requirement: Freshers or entry-level candidates with 0 to 1 year of statistical programming experience.
• Programming Foundation: Fundamental knowledge of Base SAS, SAS/STAT, SAS Macros, or modern data programming in Python/R.
• Analytical Aptitude: Strong understanding of descriptive statistics, hypothesis testing, and clinical trial design concepts.
• Attention to Precision: High diligence in cross-verifying statistical outputs against clinical study protocols.

Key Responsibilities

Your core duties as an Associate Statistical Programmer will include:

1. Statistical Program Development: Write SAS scripts to process raw clinical patient data collected during trial phases.
2. CDISC Data Standard Implementation: Map and transform operational data into standard CDISC SDTM (Study Data Tabulation Model) and ADaM (Analysis Data Model) datasets.
3. Table, Listing, and Figure (TLF) Generation: Program standard demographic tables, adverse event summary tables, and efficacy graphs for clinical study reports.
4. Independent Quality Control (QC): Perform peer code review and independent programming validation to verify that outputs generated by senior programmers match expected numerical values precisely.
5. Specification Documentation: Maintain clear programming documentation, traceability logs, and data definition files (define.xml).

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Skills Required

• SAS Programming: Familiarity with DATA step processing, SQL procedures (PROC SQL), reporting procedures (PROC REPORT, PROC TABULATE), and macro facility.
• Statistical Principles: Knowledge of summary statistics, p-values, confidence intervals, and regression models.
• Data Hygiene: Methodical approach to handling missing data values, outliers, and schema transformations.
• Regulatory Awareness: Basic awareness of ICH-GCP guidelines and clinical trial phases (Phases I through IV).
• Communication Skills: Professional collaboration skills to coordinate with biostatisticians and medical writing teams.

Salary & Benefits

ICON offers structured career progression and compensation packages designed for analytics professionals:

• Expected Starting CTC: Approximately ₹4.5 LPA to ₹6.0 LPA, based on technical evaluation.
• Comprehensive Healthcare: Medical insurance covering self, spouse, and children, along with annual wellness benefits.
• Professional Training: In-depth training on advanced CDISC standards, automated statistical validation pipelines, and clinical domain expertise.
• Work Culture: Dynamic and inclusive global research environment located in Bangalore.

Day in the Life of a Statistical Programmer

Your day begins with a review of trial deliverable timelines with your lead biostatistician. You open the SAS Studio interface to inspect raw data extracts uploaded from global clinical trial sites. You write a SAS macro to map patient vital signs into standard SDTM VS domains, verifying each parameter against the study protocol specification. After generating an adverse events table, you send your log file to a validation partner for double programming verification. In the afternoon, you attend a team learning seminar on automating R-based clinical visualizations. You conclude by logging your programming deliverables in the study tracking repository.

Who Should Apply and Who Should Skip

Who should apply:

• Graduates in Statistics, Mathematics, or Data Science who want to apply quantitative skills to healthcare and drug development.
• Candidates who enjoy structured coding, statistical analysis, and regulatory precision.
• Freshers aiming for recognized careers as Biostatisticians or Principal Statistical Programmers.

Who should skip:

• Those looking for generic web development or mobile app building.
• Candidates who dislike rigorous compliance protocols and detailed documentation.
• Individuals with no interest in statistics or health sciences.

Interview Preparation and Sample Questions

Interviews focus heavily on Base SAS basics, SQL queries, and fundamental statistical concepts. Check our aptitude preparation guide before appearing.

Sample Questions:

1. "Explain the compilation phase versus execution phase of a SAS DATA step."
2. "What is the difference between MERGE and UPDATE statements in SAS?"
3. "How do you handle duplicate records in a clinical dataset using PROC SORT?"
4. "What are CDISC SDTM and ADaM models, and why are they required by regulatory authorities?"

How to Apply Step by Step

1. Open the official ICON Plc career listing via the link provided below.
2. Review the criteria for Reference: JR163286 (Associate Statistical Programmer).
3. Click "Apply" and upload your curriculum vitae.
4. Ensure your academic projects involving statistical modeling or SAS/R/Python are clearly detailed. Safeguard yourself against job fraud by reading our fake job offers alert guide.

Tips to Crack It

• Emphasize Base SAS certification (if completed) or relevant academic statistical coursework.
• Practice writing clean SQL queries and basic data manipulation logic.
• Highlight any academic research papers, thesis work, or data analysis internships.

Related Guides and Reading

• Resume Formatting Tips for Data and Science Graduates
• Off Campus Hiring Trends in India
• How to Prepare for Quantitative and Analytical Tests
• Guide to Spotting Job Scams in Healthcare and IT

Understanding CDISC Standards in Clinical Programming

The Clinical Data Interchange Standards Consortium (CDISC) establishes global data standards that enable pharmaceutical companies and regulatory agencies (FDA, EMA, PMDA) to review drug safety and efficacy seamlessly. Mastering these standards forms the bedrock of a successful career as a statistical programmer.

During your tenure at ICON, you will work extensively with:

• CDISC SDTM (Study Data Tabulation Model): The foundational standard for organizing and formatting clinical trial tabulation data. SDTM defines standard domains such as Demographics (DM), Adverse Events (AE), Concomitant Medications (CM), and Vital Signs (VS).
• CDISC ADaM (Analysis Data Model): Datasets optimized for statistical analysis and visualization. ADaM datasets (such as ADSL for subject-level analysis and ADAE for adverse event analysis) feature derived variables, baseline flags, and imputed time points.
• Define.xml and Reviewers Guides: Comprehensive machine-readable metadata documentation detailing data origin, derivation rules, and variable attributes submitted alongside datasets to government agencies.

Practical 7-Day Self-Study Plan for Aspiring Statistical Programmers

If you are preparing for technical assessments and interviews at ICON, follow this focused preparatory schedule:

• Day 1: Core SAS DATA Step mechanics, execution loops, program data vector (PDV), and variable attributes (LENGTH, FORMAT, LABEL).
• Day 2: Subsetting, conditional logic (IF-THEN/ELSE, SELECT-WHEN), and processing missing values.
• Day 3: SAS procedures for data manipulation and sorting (PROC SORT, PROC FORMAT, PROC TRANSPOSE).
• Day 4: Combining datasets (MERGE with IN= tracking variables, concatenation, and updating).
• Day 5: Advanced SQL in SAS using PROC SQL (joins, subqueries, group calculations, and macro variable creation via INTO:).
• Day 6: Fundamental SAS Macros (%MACRO, %MEND, macro variables, %LET, and macro debugging options).
• Day 7: Overview of clinical trial phases, biostatistical definitions (Odds Ratios, Kaplan-Meier curves, p-values), and mock interview practice.