Communicate with the Product and Management teams to understand business requirements and user problems
Carry out EDA in collaboration with the Analytics team to identify solutions and research industry best practices and tools for its implementation
Build data ingestion pipelines, models and serving layers, and deploy them by working closely with the Tech team
Communicate the solutions business impact, caveats and implementation deadlines to all stakeholders
Broadly 60%-70% of time dedicated to Model Deployment work-streams and rest to Model Development
Must Haves:
3-5 years experience in developing, delivering and maintaining data-driven solutions (Ex: recommendation systems, traffic forecasting, dynamic pricing, video and text processing)
Good understanding of fundamental statistics and ML concepts (Ex: hypothesis testing, linear and ensemble models, graph analytics, deep learning)
Expert-level grasp on Python programming language and SQL (Ex: OOPs, async-await paradigm, CTEs, window functions)
Hands-on experience with creating data ingestion pipelines and APIs that serve model results at scale (Ex: Spark, FastAPI, Celery)
Ability to break down business requirements into technical problems and communicate solutions to other teams
Good to Haves:
Bachelors degree in a quantitative discipline - Engineering, Statistics, Mathematics, Economics etc.
Ability to identify and integrate innovative tools which can help build more efficient solutions
Love for sports
Experience building NLP and computer vision applications