Data Scientist (ML)

TL;DR

Data Scientist (ML): Design and implement ML models for forecasting, recommendation systems, pricing, and churn with an accent on scalable workflows, production deployment, and model monitoring. Focus on performing EDA, collaborating with stakeholders, communicating insights, and integrating models with product and engineering teams.

Location: Remote (work from anywhere)

Company

Dynamic startup crafting innovative Big Data and Machine Learning systems for demand planning, budget forecasting, e-commerce ads, visual recognition, and personalized recommendations.

What you will do

• Design and implement ML models for business needs like forecasting, recommendations, pricing, and churn prediction.
• Perform exploratory data analysis to identify trends, anomalies, and data relationships.
• Collaborate with stakeholders to define problems, metrics, and data requirements.
• Build scalable ML workflows, deploy models to production, and monitor performance.
• Communicate insights to technical and non-technical audiences.
• Work with product, engineering, and business teams to integrate models and mentor juniors.

Requirements

• Expert Python for data analysis and ML modeling.
• Hands-on with ML libraries/frameworks, supervised/unsupervised learning, time series, A/B testing.
• Experience deploying and maintaining production ML models.
• Production-grade, reproducible code proficiency.
• Solid SQL knowledge for structured/unstructured data.
• Strong communication of technical concepts to stakeholders and cross-functional collaboration.
• Git and agile practices experience.

Nice to have

• Recommendation systems, dynamic pricing, or customer segmentation.
• Cloud platforms (AWS, GCP, Azure) and ML services.
• Docker, Airflow/Prefect, MLflow, observability tools, CI/CD for ML.
• Poetry or uv.

Culture & Benefits

• Remote-first culture – work from anywhere.
• In-company English lessons.
• Wellhub/sports club stipend, food credits via Pedidos Ya.
• AWS, DBT, Google Cloud, Azure, Databricks certifications covered.
• Birthday off + extra vacation week (Mutt Week), referral bonuses, annual team trip.