Job Summary :
Analyzes the data needs of enterprise to build, optimize and maintain conceptual ML / Analytics models. Data scientist provides expertise in modeling & statistical approaches ranging from regression methods, decision trees, deep learning, NLP techniques, uplift modeling; statistical modeling such as multivariate techniques.
Roles & 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 Experience :
Strong experience (3+ years) with Building statistical models, applying machine learning techniquesExperience (3+ years) on Big Data technologies such as Hadoop, Spark, Airflow / DatabricksProven experience (3+ years) in solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.Proven experience (3+ 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 timeEnsure 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