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Statistical Programmer with 4+ years in Clinical SAS, R & CDISC Standards
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Clinical SAS - R Programmer with 4.3+ years of experience in clinical trial data analysis and R programming. Strong hands-on expertise in SAS on R programming, CDISC standards (SDTM, ADaM), and TLF development for oncology and endocrinology studies. Experienced in end-to-end clinical data processing, validation, and regulatory-compliant deliverables aligned with ICH TMF(Trail master file) and FDA guidelines. Proven ability to collaborate with bio-statistics and clinical teams in CRO and pharma environments.
Jawaharlal Nehru Technological University – Kakinada (JNTU-k)
B. Pharmacy · Pharmaceutics
August 1, 2009 – June 30, 2013
WATERLABS.AI .PVT. LTD
DATA ANALYSIS
February 1, 2026 – May 31, 2026
Bengaluru, Karnataka, India
UPTEC INFORMATION TECHNOLOGY PVT LTD
Statistical Programmer
September 1, 2022 – January 31, 2026
Hyderābād, Telangana, India
covalent technology
Internship - oncology clinical trials
January 1, 2022 – September 30, 2022
Hyderābād, Telangana, India
MINAXY PHARMACY
Chemist
July 1, 2015 – October 31, 2016
Hyderābād, Telangana, India
E4E MEDICAL CODING
Medical Coding Associate
May 1, 2014 – May 31, 2015
Chennai, Tamil Nadu, India
Cultural Fit Analysis
The candidate's experience is highly specialized in clinical data programming, which aligns well with roles requiring deep expertise in this domain. The transition from pharmacy and medical coding to statistical programming demonstrates adaptability and a focused career shift. The project diversity within clinical trials (oncology, endocrinology) shows breadth within the niche. The target role 'Specialist Programmer' aligns with the candidate's specialized skill set in R, SAS, and CDISC standards.
Soft Skills & Operational Fit
The resume indicates experience in collaborative environments (working with bio-statistics and clinical teams). The detailed descriptions of clinical data processing, validation, and regulatory compliance suggest an organized and detail-oriented approach. However, without psychometric test results, a comprehensive assessment of work attitude, stress handling, and team collaboration is not possible.