• Own the Permissions & Privacy Framework – Serve as the single business owner of client data permissions and governance, defining role-based access principles and clear decision rights. Evolve the framework as appropriate • Operationalize Access & Policy Management – influence the design and manage workflows for access provisioning, deprovisioning, temporary access, advisor transitions, and confidential client handling • Govern Ongoing Permission Decisions – Act as the central project manager for complex access requests. Maintain clear policy guidance for recurring scenarios. • Build Audit, Monitoring & Risk Controls – Establish audit processes, reporting, and monitoring to ensure consistency and detect inappropriate access • Drive Cross-System Alignment – Partner with Product and Technology teams to standardize permissions across all platforms and products • Enable the Organization – Partner to create training, guidance, and FAQs to ensure employees understand access policies and processes.

• Understand sponsor data needs and be able to translate these requirements into necessary analytics • Proactively specify algorithms, models, analyses, and output required to meet sponsor needs • Draft business requirement documents and specifications. • Anticipate reporting and analytic needs to support sponsors • Understand CDISC standards and clinical trial submission processes and be able to produce data transfers and trial documentations to these standard independently • Confidence to present results and interpretations independently to sponsors • Ability to explain complex data concepts in an easily understandable way • Skilled at summarizing data in succinct, effective presentations and executive summaries. • Independently manage numerous data analytic projects and deliverables concurrently • Build, develop, and deploy data analytics, data models, reporting systems, data automation systems, dashboards and performance metrics. • Maintain reporting systems and dashboards. • Support the creation of data visualization tools. • Draft and implement Statistical Analysis Plans. • Monitoring of study data • Data transformation, transposition, cleaning, curation and reprocessing in support of data transfers and delivery to sponsors. • Implementation of CDISC data standards including SDTM and ADaM datasets. • Interact with sponsors to resolve scientific queries and participate in study planning. • Write clinical study reports, analytic reports, and other scientific reports. • Contribute to data curation and aggregation. Provide requirements and documentation of data structure and needs to support data analytics. • Analyze and report on cognitive outcome measures and cognitive tests. • Develop and QC statistical and programming output while maintaining rigorous quality standards. • Interact with project management, statistics, data management, statistical programming, and site services teams internally to support scientific analysis and reporting and support data related questions. • Develop solutions to unique customer requests relating to topics such as stratification, inclusion, reliable change monitoring, data monitoring, normative data, and other cognitive testing applications. • Generate clinical study report summary tables, data listings, figures, and other output as specified in the statistical analysis plan or other scientific reporting specification. • Review and monitor cognitive data rater performance, data monitoring findings, custom programming/statistical analysis, normative data, z-scores and computations. • Analyze and interpret cognitive data from clinical trials and research studies. • Critically evaluate internal processes and scientific methodologies. • Contribute to the development of processes, technology, and infrastructure which support the functions of scientific services and related operations. • When acting as a QC programmer, work independently from source data and ensure a 100% match of all output. • Maintain an intimate knowledge of Cogstate’s data systems. • Provide requirements for development and commercialization of new technology.

• Estruturar e manter bancos de dados, garantindo a integridade, organização e disponibilidade das informações; • Desenvolver e executar processos de ETL (extração, transformação e carga de dados); • Realizar data cleansing e feature engineering para preparação de dados analíticos; • Extrair, tratar e analisar grandes volumes de dados provenientes de diferentes fontes; • Desenvolver estudos analíticos e análises ad hoc para apoiar a tomada de decisão; • Construir, validar e implementar modelos preditivos utilizando técnicas de Machine Learning; • Traduzir necessidades de negócio em soluções analíticas baseadas em dados; • Colaborar com equipes multidisciplinares para identificar oportunidades e gerar insights estratégicos.

Role Description We are seeking a highly skilled Senior Data Scientist to join a fast-paced SaaS organization on a contract basis. This role is ideal for a hands-on data science professional with deep expertise in machine learning, Snowflake Cortex ML, Python, advanced SQL, and MLOps automation. The successful candidate will partner closely with business stakeholders to develop, optimize, and deploy production-grade machine learning solutions that drive business value. This is a 3 to 6-month contract with potential for permanent conversion, targeting a start date of August 1. Key Responsibilities - Machine Learning & Data Science - Design, develop, and enhance production-grade machine learning and predictive analytics models to solve complex SaaS business problems. - Maintain, optimize, and evaluate existing ML models to ensure continuous improvements in accuracy, performance, and scalability. - Apply statistical modeling and advanced machine learning techniques to extract actionable business insights from enterprise data. - Snowflake Cortex ML Development - Develop, deploy, and scale machine learning solutions natively using Snowflake Cortex ML and its broader AI capabilities. - Optimize model execution, feature engineering, and data processing architectures directly within the Snowflake ecosystem. - Collaborate with data engineering and platform teams to seamlessly integrate Cortex ML and Snowpark workflows into production systems. - MLOps & Pipeline Automation - Build, automate, and maintain robust end-to-end machine learning pipelines for model training, validation, and deployment. - Implement and govern MLOps workflows to support automated model monitoring, versioning, retraining, and continuous integration/continuous delivery (CI/CD). - Improve the reliability, automation, and scalability of production machine learning environments using Jupyter Notebooks and orchestration tools. - Data Integration & Stakeholder Collaboration - Perform complex SQL-based data extraction, transformation, feature engineering, and integration of third-party data sources. - Partner directly with cross-functional stakeholders in Product, Engineering, and Business teams to translate operational requirements into technical AI solutions. - Document workflows and present clear technical findings, methodologies, and strategic recommendations to both technical and non-technical audiences. Qualifications - 7 or more years of professional experience in Data Science or Machine Learning. - Demonstrated experience developing, optimizing, and supporting production-grade machine learning and predictive models. - Strong industry experience within a Software-as-a-Service (SaaS) or modern digital product environment. - Hands-on experience building and deploying machine learning solutions utilizing Snowflake Cortex ML. - Expert-level programming skills in Python and advanced SQL querying. - Proven experience establishing and automating MLOps pipelines, including model deployment, monitoring, versioning, and CI/CD. - Strong background in data integration, data quality verification, and advanced feature engineering. - Experience collaborating directly with business stakeholders to translate business needs into technical AI and ML solutions. Preferred Qualifications - Hands-on experience with Large Language Models (LLMs) or Generative AI integrations. - Experience utilizing Snowpark and modern Snowflake AI/ML platform capabilities. - Practical familiarity with Git, version control systems, and enterprise data pipelines. - Experience using cloud-based AI platforms and advanced production analytics tools. Core Skills & Attributes - Exceptional analytical, problem-solving, and statistical modeling capabilities. - Strong communication and presentation skills, with the ability to translate technical AI concepts into clear business value. - Excellent stakeholder management and collaboration skills across cross-functional engineering, product, and business domains. - Self-motivated with a strong attention to detail and the ability to operate independently in a fully remote environment. Benefits - Competitive salary - Remote location - Senior Level (7 or more years of experience)