Quantitative Risk Analyst

About us

At Koltin, we’re redesigning the way we care for our moms, dads, and grandparents to help them remain healthy and independent for as long as possible.

How do we do it? Through our health memberships, which provide personalized, preventive care to support our members’ long-term well-being.

We are the first company in Mexico offering health memberships that include major medical insurance coverage for older adults-up to 84 years old-backed by BBVA Seguros Salud.

About the role

The Quantitative Risk Analyst at Koltin applies statistical and actuarial thinking to our health insurance data—turning raw claims, clinical records, and member histories into rigorous risk insights.
This is a role for someone who is genuinely fascinated by probability, distributions, and the mathematics of risk—not just someone who has those on a résumé. You'll work on questions like: How do we estimate the expected cost of a new member cohort? What
does the claims distribution look like by age band and chronic condition? Are we reserving correctly? What does the data say about the effectiveness of our prevention programs?
You will collaborate closely with our Data Scientist, actuaries, and clinical team to build experience studies, design statistical analyses, and generate quantitative evidence that shapes pricing, reserving, and prevention strategy.
Ideal backgrounds: Actuarial Science, Statistics, Mathematics, Economics (quantitative), Physics. The ideal candidate is someone who genuinely loves the statistical and actuarial side of the problem—not primarily an engineer or a software builder.

You’re a good fit if you:

Identify with our Values: Ownership, Collaboration, Excellence, Data-driven, Curiosity.

Are genuinely drawn to the mathematics of risk: you find probability distributions, survival curves, and loss ratios intrinsically interesting.

Are statistically rigorous: you don't just report a mean—you think about the distribution, the sample size, the confidence interval.

Know when a result is too good to be true—and have the instinct to investigate rather than celebrate.

Can communicate statistical uncertainty clearly to non-statisticians, without dumbing down the substance.

Are collaborative: you work well with actuaries, clinicians, and data engineers, even when they think differently than you do.

Are curious about healthcare and insurance as domains: you want to understand how claims work, how risk pools behave, how prevention changes outcomes.

Are comfortable in a startup environment where data definitions evolve, tools
change, and not everything is documented.

Communicate well in Spanish & English.

Had experience with:

Statistical modeling in R or Python: GLMs, survival models, time-series, bootstrap methods.

Actuarial or statistical analysis of claims or health data: frequency/severity, loss ratios, experience studies.

Survival analysis: Kaplan-Meier, Cox proportional hazards, accelerated failure time models.

Probability distributions: fitting, testing, and reasoning about distributional assumptions.

SQL for data extraction and preparation.

Communicating quantitative findings clearly through tables, charts, and written summaries.

(Nice to have) Actuarial exams in progress or completed (VEE credits or exam-level knowledge of probability and statistics).

(Nice to have) Experience with reserving methods: development triangles, Bornhuetter-Ferguson, chain-ladder.

(Nice to have) R packages: survival, fitdistrplus, actuar, lme4, or equivalents.

Key Outcomes:

Experience studies are built and maintained: claims rates by age, condition, cohort, and time—with proper statistical confidence.

Claims frequency and severity distributions are estimated and documented; deviations from expected are flagged and investigated.

Statistical analyses directly support pricing decisions, reserving reviews, and prevention program evaluations.

Survival analyses of health deterioration events inform clinical pathway design and early intervention timing.

Risk segmentation is backed by statistical evidence: not just intuition or business rules.

Actuaries and leadership have reliable quantitative inputs that improve the quality of risk decisions.

Methodologies are documented so analyses can be reproduced, audited, and built upon over time.

How we hire:

Note: There might be a couple more steps in between if we see the need.

1. Initial conversation with a recruiter (15–20 min)

An intro call to get to know you, understand your background, and share context about the role, the team, and Koltin.

2. Asynchronous technical exercise (time-boxed)

A real-world–inspired scenario to understand how you:

Structure problems

Analyze data

Communicate insights and recommendations clearly

We focus on reasoning, clarity, and trade-offs—not just the final answer.

3. Discussion with our Principal, Data Strategy (60 min)

A deeper conversation on:

Technical and analytical depth

Decision-making and prioritization

Data quality, metrics, and operational thinking

4. Conversation with our VP of Product Engineering (30 min)

This conversation focuses primarily on cultural fit and how you operate day to day, including:

Communication skills: clarity, structure, and ability to adapt your message to different audiences

Problem orientation: how you frame ambiguous problems and turn them into actionable analyses

Ownership and accountability: how you take responsibility for outcomes, not just analyses

Collaboration style in a cross-functional environment

5. Final conversation with one of our founders (30  min)

We close the loop with a discussion around vision, culture, and long-term fit, and how you see yourself growing with Koltin.

Perks & Benefits:

🎓Access to professional development tools and resources (courses, books, workshops, etc.)

💊Unlimited virtual medical assistance (general practitioner, nutritionist, psychologist) for you and 3 family members

🏈 Access to physical wellness tools (TotalPass)

🌴 9 extra vacation days per year in addition to the legal minimum

👓 Private Major Medical Insurance

💻 All the equipment you need to do your best work

💵 $500 MXN monthly support for home office expenses

💎 One-time $2,000 MXN support to set up your home workspace

Being aware that some groups don’t apply even if they are qualified, this is a reminder to apply even if you think that you don’t tick all the boxes!

*Advanced Spanish proficiency is strongly preferred for this role.