Data Scientist

Alchemer•Louisville, CO

About The Position

We’re looking for a Data Scientist who thrives at the intersection of innovation and real-world impact. This role is focused on building, testing, and refining algorithms and machine learning models that power product experiences at scale. You’ll work closely with Product and Engineering to turn complex data problems into production-ready solutions. From developing full-scale algorithms to fine-tuning models, your work will directly influence products used by tens of thousands of users globally. If you’re someone who thinks AI is exciting and also wants to understand what’s happening under the hood and build it yourself, this role is for you.

Requirements

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
3–5 years of hands-on data science experience, ideally in a SaaS or product-driven environment
Strong programming skills in Python, with working knowledge of SQL and mongoDB
Familiarity with modern AI/ML frameworks and tools
Proven experience building and deploying machine learning models and algorithms, including experience with LLM-based model deployment
Experience working in production environments and collaborating with engineering teams to ship solutions
Solid understanding of statistical modeling, data structures, and algorithm design
Experience with training regression, classification, and clustering models
Comfortable working in the command line and modern development workflows
Ability to think critically about problems and develop end-to-end solutions, not just isolated analyses
Strong curiosity and a mindset of going above and beyond to solve complex problems

Nice To Haves

Prior experience in a SaaS or B2B product environment
Experience or an interest in LLM-accelerated coding tools

Responsibilities

Design, develop, and optimize machine learning models and algorithms for real-world product applications
Translate ambiguous business problems into scalable data science solutions that drive measurable outcomes
Work hands-on in the command line and development environments to build, test, and iterate on models
Partner with Product and Engineering teams to productionize models and integrate them into customer-facing applications
Continuously evaluate and improve model performance, accuracy, and scalability
Go beyond surface-level solutions to deeply understand data, model behavior, and algorithm performance
Stay current with advancements in AI/ML and apply them thoughtfully to business problems
Balance innovation with execution, ensuring solutions are both cutting-edge and aligned to business objectives