Role Description ClinChoice is searching for a Clinical R Programmer/Principal Data Scientist Consultant to join one of our clients. We are seeking a Principal Data Scientist Consultant with strong experience in R and a solid background in clinical programming. The ideal candidate will have hands-on experience developing SDTM and ADaM datasets using R, along with working knowledge of SAS. This role requires someone who can support clinical trial deliverables, ensure regulatory compliance, and collaborate closely with biostatistics and clinical data teams. - Develop, validate, and maintain SDTM and ADaM datasets using R following CDISC standards. - Support TLF (Tables, Listings, Figures) generation in R or SAS as needed. - Write efficient, reproducible, and well-structured R scripts for clinical data analysis and reporting. - Collaborate with statisticians, data managers, and clinical teams to understand programming requirements. - Perform QC checks, reconcile data issues, and ensure deliverables meet regulatory expectations (e.g., FDA, EMA). - Contribute to programming workflows, documentation, and version control best practices. - Support automation initiatives and R-based pipeline development. - Utilize SAS for legacy studies or where SAS support is required. Qualifications - Bachelor’s or Master’s degree in Statistics, Computer Science, Mathematics, Life Sciences, or related field. - 4–6+ years of experience in clinical programming, with a strong focus on R. - Proven experience in creating SDTM and ADaM datasets using R. - Working knowledge of SAS programming. - Solid understanding of CDISC standards (SDTM, ADaM). - Experience with clinical trial data, regulatory submissions, and QC processes. - Strong analytical, problem-solving, and documentation skills. Requirements - Experience with R packages such as tidyverse, haven, pharmaverse (e.g., admiral, tidyCDISC), or other clinical programming toolkits. - Understanding of R Markdown, Shiny apps, or reproducible reporting tools. - Exposure to GxP validation, version control (Git), and automated workflows. - Experience working in a CRO or pharmaceutical environment. Company Description ClinChoice is a global full-service CRO specializing in clinical development and functional solutions for pharmaceutical, biotechnology, medical device, and consumer health companies. We have over 28 years of proven high-quality delivery and results across all our services, with over 4,000 professionals in more than 20 countries across the Americas, Europe, and Asia-Pacific. Our mission drives our culture: to contribute to a healthier and safer world by accelerating the development and commercialization of innovative drugs and devices. Our employees are the most valuable company asset, and they are the fulcrum around which all ClinChoice activities are built, and close management and training are the core instruments to develop and maintain highly-qualified personnel. The continuous training keeps the resources qualified in terms of competence and expertise and gives all personnel the clear tools needed to manage both internal and client processes with the same methodology. The success of these core values is evidenced by our low industry-average turnover rates. ClinChoice is an equal opportunity employer. We have based our success on attracting, developing, and promoting talent, guided by a commitment to diversity and inclusivity. Our employees come from very diverse backgrounds: gender, race, beliefs, and ethnicities. We recognize this is our strength and celebrate it.

Role Description As a Senior Data Scientist at the Experian Innovation Lab, your role will be to research and develop analytical solutions, prototype new products, and evaluate data assets. You must bring an experience in predictive modeling, machine learning, and deep learning to this position. You will report into the Sr. Principal Data Scientist. You'll have the opportunity to: - Create advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources. - Unearth data value by selecting and applying the right machine learning, deep learning and processing techniques. - Refine data manipulation and retrieval through the design of efficient data structures and storage solutions. - Innovate with tools designed for data processing and information retrieval. - Dissect and document vast datasets, analyzing them to highlight patterns and insights. - Solve complex challenges by developing impactful algorithms. - Ensure model excellence by validating performance scores and analyzing Return on investment and benefits. Qualifications - PhD degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field. - 2+ years of experience in AI, data science, or predictive modeling. - Proficiency in multiple programming languages, including Python. - Experience in deep learning (CNN, RNN, LSTM, attention models), machine learning methodologies (SVM, GLM, boosting, random forest), graph models, or reinforcement learning. - Experience with open-source tools for deep learning and machine learning technology such as pytorch, Keras, tensorflow, scikit-learn, pandas. - Experience with large data analysis using pySpark. - Experience with LLMs and the relevant tools in the Generative AI domain. - Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, mongoDB, Cassandra. - Experience modifying and applying advanced algorithms to address practical problems. - Experience with online, mobile marketing analytics. - Experience with GPU programming. Benefits - Great compensation package and bonus plan. - Core benefits including medical, dental, vision, and matching 401K. - Flexible work environment, ability to work remote, hybrid or in-office. - Flexible time off including volunteer time off, vacation, sick and 12-paid holidays.

• Lead a data science team and cross-functional projects • Innovate and improve machine learning models • Partner with business leaders and technical experts across the company • Develop new data sources and improve our modeling methodology • Apply models with sound risk management

• Partner directly with CX directors, managers, and executive leadership to deliver prescriptive, data-backed guidance for strategic planning. • Analyze customer health scores, product usage, and support trends to perform deep-dive retrospective analyses on churn and contraction drivers. • Design and execute impact measurement models that move past baseline usage metrics to quantify actual gross retention rate (GRR) improvements, net revenue retention (NRR) gains, and process efficiencies. • Lead the quantitative analysis for complex special projects, including annual account carves, territory balancing, and customer segmentation strategies. • Using Large Language Models (LLMs) to rapidly prototype scripts, automate ad-hoc reporting requests, and build lightweight data workflows. • Actively leverage the native AI components within Snowflake and our broader business intelligence stack to accelerate context gathering and surface predictive customer trends. • Map out how multi-source data flows between our primary platforms to create a unified, accurate view of the post-sales ecosystem. • Write high-performance, production-grade SQL queries directly within Snowflake to manipulate and model complex datasets. • Serve as part of the core CX liaison to the Enterprise Data & Analytics (ED&A) team, owning downstream data requirements and standardizing metric definitions.