Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design rigorous statistics problems reflecting professional practice; - Evaluate AI solutions for correctness, assumptions, and constraints; - Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); - Improve AI reasoning to align with industry-standard logic; - Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. - 3+ years of professional mathematics experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Payment - Paid contributions, with rates up to $73/hour*  - Fixed project rate or individual rates, depending on the project - Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

• The Manager, Predictive Analytics and Data Science is responsible for serving as the leader, subject matter expert, teacher, and mentor of the Predictive Analytics and Data Science team. • Lead a team of data scientists and analysts to develop and execute predictive analytics projects and initiatives • Collaborate with cross-functional teams, including IT, healthcare operations, finance, and clinical teams, to identify opportunities for data-driven solutions and predictive modeling applications • Develop and implement predictive models, algorithms, and statistical techniques to extract insights from large and complex healthcare datasets • Utilize machine learning algorithms to identify patterns, trends, and opportunities for improving operational efficiency, cost containment, and patient care • Utilize Natural Language Processing (NLP) algorithms and techniques to process and analyze unstructured healthcare data, such as clinical notes, patient feedback, and medical literature, to extract meaningful insights • Conduct rigorous data analysis, including data cleansing, feature engineering, and exploratory data analysis, to derive meaningful insights and actionable recommendations • Stay abreast of emerging trends, tools, and techniques in predictive analytics, data science, and healthcare informatics to drive innovation and continuous improvement • Collaborate with stakeholders to define key performance indicators (KPIs), develop metrics, and create dashboards and reports that effectively communicate insights and support decision-making • Provide strategic guidance and recommendations to senior leadership based on data analysis and predictive modeling results • Mentor and develop team members, fostering a collaborative and innovative work environment • Ensure compliance with data privacy and security regulations and maintain the highest standards of data integrity

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