Job Description

Role Description

Healthcare is in crisis and the people behind the results deserve better. Junction is building the infrastructure layer for diagnostic healthcare, making patient data accessible, actionable, and automated across labs and devices. Our mission is simple but ambitious: use health data to unlock unprecedented insight into human health and disease.

If you're passionate about how technology can supercharge healthcare, you’ll fit right in.

Short on time? TL;DR

• You can define what should be measured, how it should be modeled, and how those insights should shape product and company decisions.

Ownership:

• You’ll own Junction’s highest-leverage statistical, modeling, and evaluation work across diagnostics, clinical workflows, and AI-enabled product development.

Scope:

• This is not a pure IC modeling role and not a reporting role.
• You’ll set the methodology, research roadmap, and decision framework for how Junction uses data to drive product, clinical, and business outcomes.

Salary: $180,000 – $220,000 + equity

Location: Fully remote (EST timezone only)

Why we need you:

• Junction sits in the flow of high-value diagnostics and clinical data.
• As the company grows, our advantage moves beyond just having data to having the ability to turn it into reliable intelligence improving product decisions, customer outcomes, and the performance of the business.
• Some of that work exists today, but it is not yet owned as a coherent function.
• We need someone who can define the broader scientific and analytical system: what we should measure, what methods we trust, where modeling creates real leverage, and how that work translates into products and decisions that hold up outside a demo.

We’re hiring our first Data Scientist to take ownership of, and establish that standard. This role will lead Junction’s most important modeling, experimentation, and evaluation work. You’ll partner closely with data, product engineering and leadership teams to drive the analytical roadmap by which Junction can leverage differentiated value from data.

What you’ll be doing day to day:

• Own the research and modeling work underlying Junction’s highest-priority data science opportunities across diagnostics, clinical workflows, and AI-enabled product features.
• Define rigorous frameworks for measurement, experimentation, and causal evaluation so we can distinguish signal from noise and make decisions we can defend.
• Lead development of predictive models, segmentation approaches, risk or routing logic, and other statistical systems that directly inform product and business strategy.
• Build the analytical foundation behind customer-facing features — from model development through to validation and performance tracking.
• Partner with engineering and data engineering to ensure models and analytical systems can be put in production, are reliable, and useful in real workflows.
• Establish how Junction evaluates data-driven and AI-enabled features, including methodology, quality thresholds, monitoring, and performance review.
• Communicate complex technical findings clearly to technical and non-technical stakeholders, including tradeoffs, limitations, and implications for action.

Qualifications

• Strong track record of leading high-stakes analytical work that influenced product, operational, or business decisions.
• Deep foundation in statistical inference, experimental design, observational analysis, and model evaluation.
• Strong Python and/or R skills, with experience working on large, messy real-world datasets.
• Experience building predictive or decision-support models in production or near-production environments.
• Experience partnering closely with engineering to move work from analysis or prototype into deployed systems.
• Ability to operate at both strategic and hands-on levels: defining the roadmap while also getting into the details when needed.
• Strong communication and stakeholder management skills; able to explain methods, findings, and tradeoffs to executives as well as technical peers.
• Comfort operating in a startup environment with ambiguity, limited structure, and high ownership.

Nice to have

• Experience designing, executing, and publishing research studies.
• Experience with HIPAA, PHI, or other regulatory clinical frameworks.
• Deep familiarity with modern data tooling and production workflows across warehouses, orchestration, and transformation layers.
• Experience developing, deploying, and designing evaluation frameworks for LLM or AI-powered features in customer-facing products.
• Expertise directly working with healthcare, diagnostics, lab data, wearable data, and other clinical data.
• Experience applying causal inference methods, such as diff-in-diff, propensity scoring, or instrumental variables in practice.

What this role isn’t

• Not an analytics role focused on dashboards, reporting, or one-off analysis.
• Not an ML platform role — you won’t own infrastructure or tooling.
• Not a good fit if you mainly want to experiment with models or AI ideas without being accountable for how they perform in production.
• Not a good fit if you struggle with ambiguity. Knowing what to work on is part of the job.

Benefits

• Your salary is dependent on your location and experience level.
• Generous early stage options (extended exercise post 2 years employment).
• Regular in-person offsites, last were in Tenerife and Miami.
• Monthly learning budget of $300 for personal development and productivity.
• Flexible, remote-first working - including $1K for home office equipment.
• Monthly budget of $150 to use towards a coworking space.
• 25 days off a year + national holidays.
• Healthcare coverage depending on location.

Important details before applying:

• We only hire folks physically based in GMT and EST timezones.
• We do not sponsor visas right now given our stage.

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