Data Scientist

Role overview Use data to produce useful insights and support decisions across machine learning, data engineering, or business intelligence and analytics. The role is described as senior and spans several possible specializations, so candidates may bring depth in one area rather than experience across every listed discipline.

Responsibilities - Develop predictive models, machine learning, or AI solutions, potentially including deep learning, natural language processing, optimization, and MLOps. - Build ETL pipelines and data processing workflows, and contribute to cloud infrastructure or performance tuning. - Create visualizations, track KPIs, and communicate findings through data-driven analysis. - Work with cross-functional teams to turn raw data into relevant insights. - Use statistical analysis or experimental design to guide analytical work where appropriate.

Requirements - At least 5 years of experience in data science, machine learning, data engineering, or analytics. - Strong programming skills in Python or R. - Proficiency in SQL and database management. - Experience with a cloud platform such as AWS, Google Cloud, or Azure. - Ability to explain insights and collaborate across functions. - Advanced written and spoken English.

Nice to have - Experience with MLOps tools and frameworks or real-time data processing. - Relevant tools may include TensorFlow, PyTorch, scikit-learn, MLflow, Spark, Airflow, Snowflake, Redshift, BigQuery, Kafka, dbt, Power BI, Tableau, Looker, Metabase, Pandas, or D3.js.

Benefits and work setup - Remote work and flexible scheduling. - English classes and ongoing learning opportunities. - Salary paid in USD and a day off for your birthday. - Optional office-based Friday lunches and social gatherings.