Python Analyst - Hybrid (Madrid, Spain) - Project related to the AAPP.

• Experience in Machine Learning and advanced analytics projects.

• At least 3 years of experience developing projects in Python

• At least 3 years of experience using the scikit-learn, pandas, numpy libraries

• At least 3 years of experience in developing predictive models

• At least 3 years of experience working in Big Data environments and Cloudera ecosystems with Spark, Impala, HDFS, and SQL

• At least 1 year of experience in deploying and monitoring models in production

• At least 1 year of MLOps knowledge and ML model lifecycle.

• University degree in Engineering, Mathematics, Statistics, Physics, Computer Science, or similar.

• Experience in building and maintaining data pipelines and Machine Learning using Kedro.

• 6 months of experience in traceability, versioning, and experiment tracking with MLFlow

• 6 months of experience working with Git and version control

• Work mode: Hybrid, with two days on-site in Madrid.

• Winter schedule: 8h/day Summer schedule: 7h/day

• Salary: €30,000 - €32,000 SBA.

Being part of THEWHITEAM is collaborating with a company made up of professionals with extensive experience in technological consulting.

We firmly believe that companies and clients set the path to follow in the sector, but people build it. We consider it of vital importance that our organization is based on our best asset and added value, which is our human team.

• Our collective agreement is that of Consulting Firms and Market Studies

• We have 23 days of vacation per year

• We have 14 paychecks, 12 monthly and two extras (June and December)

• As flexible compensation, we can request nursery vouchers and also medical + dental insurance.

At The Whiteam Consulting we are looking for a Python Analyst with experience in Machine Learning and advanced analytics projects to join data exploitation and predictive model development initiatives. We are looking for a profile capable of participating in the entire model lifecycle, from data analysis and processing to training, validation, deployment, and monitoring, working closely with technical and business teams to generate data-driven solutions that add value to the organization.

• Implementation of Machine Learning models (training, optimization, and validation).

• Evaluation of model performance and metric tracking data analysis, processing, and exploitation Collaboration with technical and business teams.

• Technology environment: Visual Studio Code on Linux servers Python Language data ecosystem Cloudera (Spark, HDFS and Impala). Kedro for pipeline structuring and MLflow for traceability. CI/CD with Jenkins