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About This Role
At Cogstate, we're advancing the science of brain health \- making it faster, easier, and more accurate to assess cognition across clinical trials, healthcare settings, and everyday life.
Our digital cognitive assessments are trusted by researchers, clinicians, and pharmaceutical partners around the world, helping to drive breakthroughs in neuroscience and improve outcomes for people living with neurological conditions. Founded on decades of cognitive science and backed by rigorous validation, Cogstate's assessments are used in more than 150 countries and over 2,000 clinical trials.
Our global team of experts \- spanning psychology, data science, operations, and technology \- works together to solve complex challenges in brain health assessment, always with a patient\-first mindset. Whether we're supporting a multinational Alzheimer's trial or developing tools to bring cognitive testing into routine care, our work is meaningful, collaborative, and constantly evolving.
At Cogstate, we're not just imagining the future of brain health \- we're building it.
That's why we're seeking a Senior Data Scientist accountable for supporting our data strategy, data analytics, data visualization, scientific reporting, data formatting/transfers, and our data infrastructure. This position requires strong communication and presentation abilities to understand sponsor needs, translate these into data analysis plans, program output, and to summarize and cogently present results and interpretations. The Senior Data Scientist must ensure data quality, result accuracy, and timely delivery. The Senior Data Scientist will collaborate closely with other members of the Data and Scientific Services team to develop and deliver data\-driven solutions to meet the needs of internal and external stakeholders.
Key Responsibilities
- 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 suscinct, 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.
- Test new features and bug fixes as needed related to data analytics and reporting.
Requirements
- Degree in data science, computer science, mathematics, psychology, neuroscience, statistics or a related area. MA/MS may be considered with additional experience and demonstrated proficiency.
- PhD Strongly preferred
- 5\-10 years of prior experience in industry or academic setting.
- Experience with data analysis, statistics, and scientific writing and presentation.
- Exceptional R expertise to run data analytics and advanced statistics
- Deep Python/Pyspark experience
- Predictive / ML modelling expertise
Skills, Knowledge and Specialist Expertise
- Proven ability to successfully manage a full workload across multiple\-projects independently.
- Ability to work in a fast\-paced, team\-oriented environment.
- Exceptional time and resource management.
- Data analytics, requirements gathering, and specification skills.
- Data presentation experience and skill. Confidence to present.
- Experience with cognition and/or neuropsychological testing.
What's In It For You
- Remote Work Practices: Cogstate is a virtual first company. Cogstate employees can work from anywhere where Cogstate is registered to business within the United States, Australia, or the United Kingdom!
- Generous Paid Time\-off: Cogstate employees receive 20 days of vacation leave, 10 days of personal leave and 10 paid public holidays.
- 401(k) Matching: As you invest in yourself and your future, Cogstate invests in you too: we match up to3% of your yearly salary in Cogstate's 401k program.
- Competitive Salary: We offer competitive base salaries plus additional earning opportunities based on the position.
- Health, Dental \& Vision Coverage: We've invested in comprehensive health \& dental insurance options with competitive company contributions to help when you need it most. We also offer free vision insurance for all full\-time employees.
- Short\-Term \& Long Term Disability Life Insurance: 100% employer sponsored
- Pre\-Tax Benefits: Healthcare and Dependent Care Flexible Spending Accounts
- Learning \& Development Opportunities: Cogstate offers a robust learning program from mentorships to assistance with programs to improve knowledge or obtain certifications in applicable areas of interest.
Our Culture
We bring our whole selves to work every day. We're courageous and we deliver together. We're passionate individuals who enjoy working together. We're brave enough and care enough to have the right conversations to get the best outcome and are famous for our can\-do attitude. We see challenges as opportunities and move with pace to achieve our goals.
If you're ready to help us in our journey to optimize the measurement of brain health around the world, please apply now!
Applicants with disabilities may be entitled to reasonable accommodation under the terms of the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on the company. If you need assistance in applying please email [email protected].
Privacy Notice for Job Applicants
Cogstate is committed to protecting your personal data. We collect and process your information for recruitment purposes in compliance with applicable laws, including the Australian Privacy Principles (APPs), the UK General Data Protection Regulation (UK GDPR), California Consumer Privacy Act (CCPA), Virginia Consumer Data Protection Act (VCDPA), Colorado Privacy Act (CPA), and similar laws in other jurisdictions.
For more information on how we collect, use, and protect your data, and your rights under these laws, you can find Cogstate's privacy policy by clicking here.
Salary Context
This $140K-$160K range is below the median for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At CogState, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($150K) sits 22% below the category median. Disclosed range: $140K to $160K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
CogState AI Hiring
CogState has 1 open AI role right now. They're hiring across Data Scientist. Based in Remote, US. Compensation range: $160K - $160K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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