Data Scientist

Job Description

Role & responsibilities Design ML design and Ops stack considering the various trade-offs. Statistical Analysis and fundamentals MLOPS frameworks design and implementation Model Evaluation best practices -Train and retrain systems when necessary. Extend existing ML libraries and frameworks -Keep abreast of developments in the field. Act as a SME and tech lead / veteran for any data engineering question and manage data scientists and influence DS development across the company. Promote services, contribute to the identification of innovative initiatives within the Group, share information on new technologies in dedicated internal communities. Ensure compliance with policies related to Data Management and Data Protection Preferred candidate profile Strong experience (2+ years) with Building statistical models, applying machine learning techniques Experience (2+ years) on Big Data technologies such as Hadoop, Spark, Airflow/Databricks Proven experience (2+ years) in solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks. Proven experience (2+ years) on innovation implementation from exploration to production: these may include containerization (i.e. Docker/Kubernetes) , Big data (Hadoop, Spark) and MLOps platforms. Deep understanding of E2E software development in a team, and a track record of shipping software on time Ensure high-quality data and understand how data, which is generated out experimental design can produce actionable, trustworthy conclusions. Proficiency with SQL and NoSQL databases, data warehousing concepts, and cloud-based analytics database (e.g. Snowflake , Databricks or Redshift) administration