Graduate Data Analyst

We're looking for a Data Analyst who thinks like a researcher: someone who can structure messy problems, build analyses that hold up, and explain them to people who don't speak in code. We care more about how you think than about a specific pedigree, and we especially value people who apply ideas from one field to solve problems in another.

What You'll Be Doing ? Problem Framing: tackling complex problems with little description or supporting information and shaping them into clear research questions, then finding your own route to a solution. ? Data Analysis:
Working with raw data to identify patterns, build models, and produce analysis that holds up to scrutiny. ? Cross-Field Application – Bringing methods from one discipline to bear on problems in another, using unexpected tools to solve them. ? Coding & Tooling – Building and running analysis primarily in Python and SQL. ? Client Communication – Explaining technical work and findings clearly to non-technical members of clients' teams.

? Continuous Learning – Picking up new domains and techniques quickly as the work demands, changing from client to client. What We're Looking For ? A STEM background (physics, mathematics, engineering, biology, or chemistry) ? Experience in applying ideas from scientific fields to tackle problems in other areas, bringing creative insights to the problem-solving process. ? Research-based experience such as lab internships, research fellowships, publications, or time at research institutions leading research and experimentation.

? Strong analytical and problem-solving abilities, including solving problems without explicit instructions ? Python (essential); SQL desirable but not critical ? Basic knowledge of data engineering and infrastructure concepts, such as AWS. ? A solid grasp of core programming concepts; exposure to lower-level languages such as C++, C, or Fortran is a plus ? Excellent numerical and written communication skills, and confidence presenting to non-technical audiences