Data Scientist (MX)

Logos is hiring a Data Scientist to jointly own its data science function, including predictive modeling, experimentation, and recommendations. The role delivers production-ready data products and partners with business and data platform teams to improve customer discovery, product use, and business outcomes.

Responsibilities

Own data science projects end to end — problem framing, method selection, modeling, validation, and presenting results to the leaders who will act on them

Ship data science work as certified, production-ready data products: models, scores, and features that other teams can trust and build on

Design, run, and interpret experiments, including hypothesis formulation, sizing, and honest reads on inconclusive results

Build and maintain predictive models and analytical pipelines in Python or R, SQL, and dbt on Databricks

Help set the data science roadmap alongside the Staff Data Scientist and the Director — including pushing back when a request won't produce value

Partner with Data Champions, the embedded analysts distributed across our business teams, so that data science output gets adopted rather than just delivered

Work with the Data Platform team to validate data quality and the reliability of upstream data products

Mentor analysts and less experienced team members, and contribute to code review and team standards

Keep documentation and reproducible code current enough that a colleague could pick up your work without you in the room

Preferred

Experience as the only data scientist — or one of very few — on a team, where you had to operate without a technical safety net

Hands-on experience with Databricks and dbt

Exposure to production ML systems, recommendation engines, or MLOps practices

Experience in a subscription or SaaS business, particularly around churn, retention, and usage analytics

Familiarity with a data mesh or distributed analytics operating model

Databricks

dbt

Production ML Systems

Recommendation Engines

MLOps

Subscription Business

SaaS

Churn Analytics

Retention Analytics

Usage Analytics

Data Mesh

Distributed Analytics

Benefits

Competitive family medical, dental, vision, and life insurance

3 company-paid holidays per year in addition to regular holidays

4 days of paid time off (PTO) per year

Paid time off (PTO) on your birthday

Law benefits (15-day Christmas bonus, vacation days established by law, 25% vacation bonus)

Awards and recognition program

Company

Bible study and sermon preparation platform for Christians

Bellingham, Washington, USA

https://faithlife.com/

Founded in 1992

201-500 employees

Qualifications

4–7 years of professional experience in data science, applied statistics, or a closely related quantitative field

A track record of owning projects independently, from ambiguous ask through delivered result, without daily oversight

A results-driven mindset: you judge your own work by measurable business impact — churn, usage, revenue — and you can tell when a model isn't earning its keep

Strong SQL and fluency in Python or R

Solid grounding in statistics and experimental design, including knowing the limits of what a given test can tell you

The judgment to prioritize: deciding what to work on, what to defer, and what to decline

Excellent communication skills, with the ability to explain technical work to non-technical audiences and to hold your position when the data supports it

Experience as the only data scientist — or one of very few — on a team, where you had to operate without a technical safety net

Hands-on experience with Databricks and dbt

Exposure to production ML systems, recommendation engines, or MLOps practices

Experience in a subscription or SaaS business, particularly around churn, retention, and usage analytics

Familiarity with a data mesh or distributed analytics operating model

4–7 years of professional experience in data science, applied statistics, or a closely related quantitative field.

Required skills

Represents the skills you have, click on the tags, Data Science, SQL, R, Applied Statistics, Experimental Design, Databricks, Dbt, Recommendation Engines, MLOps, SaaS Analytics, Data Mesh

Preferred skills

Hands-on experience with Databricks and dbt

Experience

4-7 years