Data Analytics focused roles
(at least modules 1-2 required)
A Data Analyst analyses data to tell a story and produce actionable insights for members of your team. The Data Analyst is proficient in data mining, AB testing, business intelligence reporting, and gathering and presenting insights. The Data Analyst should ideally be familiar with creating and evaluating machine learning models, understanding ETL pipelines and big data infrastructure.
Skills:
Statistics & mathematics
Data wrangling (import, clean, manipulate) and visualization
Modeling (recommended)
Technologies:
SQL
Data visualization (e.g. Tableau, Looker, Power BI)
Python, R (sometimes, Scala or Java)
Big data (e.g. Spark, Amazon EMR, Google BigQuery, Google Dataproc)
Machine Learning focused roles
(at least modules 1-3 required)
A Machine Learning Engineer designs, builds, and readies for production ML models to solve business challenges using knowledge of proven ML models and techniques. The Machine Learning Engineer is proficient in all aspects of preparing and processing data, choosing, evaluating, training, deploying, and monitoring models. The Machine Learning Engineer is familiar with creating ETL and CI/CD pipelines, understanding big data infrastructure and security.
Skills:
Modeling
Software engineering Statistics and mathematics
Technologies:
Python
Machine learning frameworks (e.g. scikit-learn, XGBoost)
SQL and databases
For deep learning focused ML engineering: deep learning frameworks (e.g. PyTorch, Tensorflow, MXNet, fast.ai)