Sr. Data Scientist

About the role

ABOUT PYYNE

Pyyne is a modern technology consultancy engineering the next generation of digital products and services.

At Pyyne, we believe in using technology to unlock business potential, create sustainable growth, and drive forward digital excellence. Our solutions range from advanced Software Engineering, Cloud, and Data & AI solutions.

JOB SUMMARY

Pyyne is seeking a Senior Data Scientist with experience building and deploying statistical and machine learning solutions to work as a consultant out of our Latin American Office. This is a high-impact role for Pyyne as we begin a new engagement with a large US-based e-commerce retailer, and this is the first technical role on the project.

A successful candidate in this role will partner with a Pyyne Project Manager and the client's head of data to turn business questions into models and analyses that stakeholders can act on.

KEY RESPONSIBILITIES

- Translate business questions from stakeholders into well-defined analytical problems, and explain findings and trade-offs clearly to technical and non-technical audiences.

- Explore, clean, and validate data from multiple sources, building reliable datasets and features for analysis and modeling.

- Design, train, and evaluate statistical and machine learning models, choosing the simplest approach that solves the problem.

- Design and analyze experiments (for example A/B tests) and define metrics that measure business impact.

- Work with the client's data and engineering teams to move models and analyses into production and keep them monitored over time.

- Write clean, tested, reproducible code and document assumptions, methods, and results so others can build on them.

- Work closely with team members to keep progress visible and raise risks early.

Must Have Skills:

- 4+ years of professional experience as a Data Scientist or in a comparable applied machine learning or advanced analytics role

- Strong Python (pandas, scikit-learn, or equivalent) and SQL

- Solid foundation in statistics and machine learning, including model selection, validation, and experiment design

- Track record of taking analyses or models from exploration to something stakeholders actually use, and explaining results to non-technical audiences

- Advanced English, spoken and written, for daily collaboration with client stakeholders

Nice to Have Skills:

- Experience in e-commerce, retail, or manufacturing use cases such as demand forecasting, pricing, or customer analytics

- Experience deploying and monitoring models in production (MLOps) on a cloud platform such as AWS, GCP, or Azure

- Familiarity with modern data stack tools such as dbt, Snowflake, BigQuery, or Databricks

- Experience with BI and visualization tools such as Tableau, Looker, or Power BI