Sr Data Scientist

Job Description

Our Tech Stack: Java, Spring, Rest API, Microservices, Kafka, Spark, NodeJS, AWS, Kubernetes, Terraform, AngularJS What you ll do Identify $ opportunities - think big picture, work with product, tech and customer-facing teams to identify the largest customer problems that can be solved using ML. Build business cases through a combination of market research and internal analytics Stakeholder relationships and strong communication - work closely with a wide variety of stakeholders to build cohesive plans and execute them. Influence senior leadership through a data-driven approach, including but not limited to market research, customer case studies and pilots/experimentation. Technical expertise, simplify complexity - build end to end ML models, be it classification/ unsupervised/ LLMs using a combination of structured and unstructured data. Work with upstream data engineering and software engineering teams to procure, process and transform data into meaningful features. Focus particularly on the data engineering aspect of the model building lifecycle. Always work backwards from the customer, to identify the simplest feasible solutions that can add maximum value. End to end ownership, delivering results - Take models into production and maintain them through effective ML engineering, demonstrate tangible business value, and deliver solutions rather than products. Qualifications- 5+ years of experience in the data science/machine learning domain, preferably with hands-on end-to-end model building experience Strong data engineering background, with ETL experience, building and maintaining pipelines, data modeling, data warehousing concepts, and familiarity with Big Data techniques Curious mind to learn, explore and identify biggest customer opportunities Build strong relationships across both technical and business/product teams, earn trust with leadership Driven towards forming opinions and conclusions through data and experimentation, rather than anecdotes and hearsay Willingness to dive deep into the tech stack as well as hands-on coding Experience in building end to end ML models, across the ML lifecycle Strong communication and leadership presence Technical skills- hands on with scripting required, with knowledge or willingness to learn tools/softwares. Knowledge of R, SQL, Python, Statistical modeling, experience with AWS/Azure/GCP ML suite Experience in the following domains/industries preferred- SaaS, ecommerce, pricing or payments Bachelors/Masters in a technical or natural sciences domain from a top university