This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role provides a unique opportunity to contribute to early-stage immuno-oncology clinical programs by leading the development and execution of statistical programming and analyses. You will ensure submission-ready study data packages, maintain compliance with CDISC standards and FDA guidance, and support internal and external stakeholders across biostatistics, clinical operations, and regulatory teams. The position offers hands-on technical work with SAS, R, Python, and Unix, while influencing program quality, efficiency, and innovation. You will operate in a collaborative, fast-paced environment, managing complex datasets, generating TFLs, and creating SDTM/ADaM outputs for regulatory submissions and publications. This contract role allows for remote work within the United States, providing both flexibility and the chance to make a tangible impact on the clinical development pipeline. - Develop specifications and execute programs for internal data reviews, publications, exploratory, post-hoc, and regulatory analyses - Ensure study data packages comply with CDISC standards (SDTM, ADaM) and health authority reporting requirements - Collaborate with clinical data management to review case report forms, database, and data transfer specifications - Create and review SDTM/ADaM mapping specifications, reviewer’s guides, and define.xml files - Generate or validate TFLs to support statistical analyses for clinical studies, regulatory submissions, and publications - Prioritize analytical deliverables strategically, including study-level or integrated analyses for safety signal detection or business needs - Manage timely and quality delivery of CRO-generated analysis results Qualifications - Bachelor’s or Master’s degree in Statistics, Mathematics, Epidemiology, Computer Science, Bioinformatics, or related field - 8+ years of programming experience in biotechnology or pharmaceutical clinical trial environments - Expert-level skills in SAS programming, with strong experience in R, Python, Unix scripts, and macro development - Solid understanding of CDISC standards (SDTM, ADaM), controlled terminology, and regulatory submission requirements - Ability to translate complex clinical and statistical problems into clear, functional code and tools - Experience with software development and testing, project management, and programming best practices - Knowledge of ICH-GCP, 21 CFR Part 11, and relevant clinical R&D concepts - Excellent written and verbal communication skills, with the ability to manage priorities and collaborate effectively Benefits - Competitive contract compensation - Flexible remote work within the United States - Exposure to cutting-edge immuno-oncology research and clinical development - Opportunity to work collaboratively with a growing Biometrics team - Professional growth through experience with regulatory submissions and complex statistical programming

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Principal Data Scientist is a senior technical leader responsible for designing advanced analytics solutions, developing machine learning models, and guiding data-driven strategies across the organization. This role combines deep technical expertise with strategic thinking to solve complex business problems using data. This role also provides technical leadership and mentorship to data scientists and analysts while shaping the organization's long-term data strategy. This is a fully remote position; however, applicants must currently reside in the United States and be legally authorized to work in the U.S. Applications from individuals residing outside the United States will not be considered. - Design and implement advanced machine learning and statistical models to solve complex business problems - Lead large-scale data science initiatives and cross-functional analytical projects - Develop predictive models, recommendation systems, and optimization algorithms - Work closely with engineering teams to deploy models into production environments - Analyze large, complex datasets to extract meaningful insights and business value - Define best practices for model development, validation, and monitoring - Guide experimentation frameworks and A/B testing strategies - Mentor and provide technical leadership to data scientists and analysts - Communicate complex technical findings to executive stakeholders - Stay current with emerging trends in AI, machine learning, and data science Qualifications - Masters or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field - 8–12+ years of experience in data science, machine learning, or advanced analytics - Strong programming skills in Python, R, or similar data science languages - Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn - Advanced knowledge of statistical modeling, predictive analytics, and machine learning techniques - Experience with big data technologies such as Apache Spark or Hadoop - Strong experience with SQL and large-scale data analysis - Proven ability to translate business challenges into data science solutions Preferred Qualifications - Experience deploying models in cloud environments such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure - Experience leading data science teams or technical initiatives - Background in building recommendation engines, NLP systems, or forecasting models - Experience with MLOps tools and model deployment pipelines - Strong experience with data visualization tools such as Tableau or Microsoft Power BI - Experience in industries such as technology, finance, healthcare, or e-commerce Compensation - Annual Salary Range: $160,000 – $210,000 USD, depending on experience, technical expertise - Additional compensation may include performance bonuses, equity, or stock options Benefits - Comprehensive medical, dental, and vision insurance - 401(k) retirement plan with employer matching - Paid time off (PTO) including vacation, holidays, and sick leave - Life insurance and disability coverage - Flexible remote work environment - Professional development and AI/ML conference sponsorships - Employee wellness and assistance programs - Potential equity or stock option grants Work Authorization Requirement - Must currently reside in the United States - Must be legally authorized to work in the United States - Applications from individuals residing outside the U.S. will not be considered

• Translate customer needs into development initiatives which you will then drive and coordinate • Work cross functionally with both customer facing teams as well as PMs and development teams • Ensure that data gets built with the highest quality and then presented in the right way through the UI • Work with smart and dedicated colleagues will ensure you are constantly challenged in this role • Drive and coordinate product development initiatives with Data and Software PMs • Develop requirements and feature specifications • Support customer-facing teams around data and product questions • Suggest improvements and new features around our data based on customer needs • Monitor data quality and identify new, relevant ways of measuring this • Coordinate and communicate across multiple teams and functions

• Translate customer needs into development initiatives which you will then drive and coordinate • Work cross functionally with both customer facing teams as well as PMs and development teams • Ensure that data gets built with the highest quality and then presented in the right way through the UI • Work with smart and dedicated colleagues will ensure you are constantly challenged in this role • Drive and coordinate product development initiatives with Data and Software PMs • Develop requirements and feature specifications • Support customer-facing teams around data and product questions • Suggest improvements and new features around our data based on customer needs • Monitor data quality and identify new, relevant ways of measuring this • Coordinate and communicate across multiple teams and functions