Member of Technical Staff, Translational Science

About the role

This role extracts scientific insights from multi-modal clinical data and supports rigorous validation. You will collaborate with cross-functional teams to shape predictive models that support precision medicine in oncology.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

Data outputs from AI models are transformed into clinical insights, and model performance is evaluated to guide improvements. These insights are synthesized into structured abstracts that prepare content for scientific meetings.

Clinical partners are engaged to define objectives, validate findings, and support real-world implementation of the research. Applications for clinical trial data access are drafted to enable research activities and ensure compliance.

Requirements

A doctoral degree in medicine or philosophy is required and must be verified through official records. High-profile scientific or clinical journals have seen lead author publications that demonstrate independent research capability at a high level. Foundational concepts of machine learning are understood at an excellent level, including model assumptions and limitations in clinical contexts. Python skills are used at an excellent level for data analysis, scripting, and reproducible workflows. Exceptional spoken and written communication skills convey complex methods clearly to diverse audiences and stakeholders. Prior experience in cancer or oncology research is viewed as a bonus for context-specific relevance and domain alignment.

Practical notes

The role is based at the New York HQ within a flat organization where initiative directly shapes leadership opportunities and ownership. Clear communication and ruthless prioritization are expected of every team member in a fast-paced research environment. Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Clinical AI tools such as causal, representation-learning, and survival-analysis models guide research workflows in digital pathology and predictive analytics. Team members operate in a research-intensive environment that spans multi-modal data and rigorous validation practices. Success depends on strong scientific judgment, rigorous validation, and close coordination with clinical and engineering partners.

Questions to ask

Useful questions for the interview: what a typical week looks like, how work is assigned, what tools the team uses, and how feedback works. Asking how the role has changed recently and what the team wishes it had known when joining is also reasonable. Questions about the manager's priorities are especially valued.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.

About the company

Ataraxis Ai is hiring for Member of Technical Staff, Translational Science. New York HQ.