Data Scientist

Creandum

New York (NY)

Remote

USD 180,000 - 220,000

Full time

14 days+

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Job summary

Junction is hiring its first Data Scientist to lead the most important modeling, experimentation, and evaluation work. You will partner with data, product engineering, and leadership to drive an analytical roadmap that turns data into actionable product and business value.

You’ll define measurement frameworks, build predictive models, and guide decisions that shape diagnostics, clinical workflows, and AI-enabled features. This is a remote-first, equity-friendly opportunity with strong ownership.

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 large real-world datasets.
Experience building predictive or decision-support models in production.
Experience partnering with engineering to deploy analytics.
Ability to operate at strategic and hands-on levels.
Strong communication and stakeholder management; explain findings to executives.
Comfortable in a startup with ambiguity and high ownership.

Responsibilities

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 to distinguish signal from noise and support defendable decisions.
Lead development of predictive models, segmentation approaches, risk or routing logic, and other statistical systems that inform product and business strategy.
Build the analytical foundation behind customer-facing features—from model development through validation and performance tracking.
Partner with engineering to ensure models can be deployed in production and used in real workflows.
Establish evaluation methods, quality thresholds, monitoring, and performance review for data-driven features.
Communicate complex findings clearly to both technical and non-technical stakeholders with clear tradeoffs.

Skills

Statistical inference

Experimental design

Observational analysis

Model evaluation

Python

Predictive modeling

Communication

Stakeholder management

Startup adaptability

Job description

Healthcare is in crisis and the people behind the results deserve better. With more and more data coming from wearables, lab tests, and patient–doctor interactions, we’re entering an era where data is abundant.

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.

Backed by Creandum, Point Nine, 20VC, YC, and leading angels, we’re working to solve one of the biggest challenges of our time: making healthcare personalized, proactive, and affordable. We’re already connecting millions and scaling fast.

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 – $200,000 + 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. Models get built. Analyses get done. Experiments answer local questions. But 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

Requirements

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 a 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

How you'll be compensated