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# Senior Data Scientist

- **Company:** KINECT, LLC
- **Location:** Los Angeles, CA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Github, Python (Programming Language), Machine Learning, Standard Sql, Software Engineering, Apache Spark, Build Management, Kinect, Feature Selection, Data Pipelines, Databricks
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pecbx8ry4c

## About the Role

* 5+ years of hands-on data science experience with a clear track record of models shipped to production
 * Strong Python (near expert-level) and solid SQL
 * Experience with Databricks and Spark in a production environment
 * Demonstrated experience in pricing, forecasting, demand modeling, or inventory optimization
 * Familiarity with time series methods and causal/experimental design
 * GitHub and software development lifecycle fluency
 * Clear, confident communicator who can present to business stakeholders

Nice to have:

 * Background in travel, hospitality, airlines, retail, or any industry where dynamic pricing is core to the business
 * Experience with double ML, elasticity modeling, or optimization engines
 * Exposure to working alongside external consultants or third-party model vendors

## Description

We're looking for a Senior Data Scientist to join a high-impact revenue science team at a well-known hospitality and travel brand headquartered in Los Angeles. This is a hands-on, production-focused role embedded in an active system build - not a research position.

You'll work directly with yield management, engineering, and external data partners to develop and deploy machine learning models that drive pricing, demand forecasting, and inventory decisions at scale.

What you'll be doing:

 * Building and deploying predictive models into a live revenue management system, owning the work from experimentation through production
 * Applying advanced ML techniques including double ML, causal inference, time series forecasting, and feature selection methods to real pricing and demand problems
 * Designing and running experiments to evaluate new data elements and model features for predictive power
 * Collaborating with yield management stakeholders to translate business objectives into data-driven solutions
 * Maintaining and extending data pipelines and model infrastructure on Databricks and Spark
 * Presenting results and defending modeling approaches to non-technical stakeholders


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