Sr. Data Scientist

Responsibilities:

• As a key partner at the table, attend key meetings with the business team to bring the data perspective to the discussions.
• Perform comprehensive data explorations around the problem to generate inquisitive insights and scope it out.
• Develop simplistic to advanced solutions to address the problem at hand.
• Build reusable code analytical frameworks to address commonly occurring business questions.
• Perform 360-degree customer profiling and opportunity analyses to guide new product strategy.
• This is a nascent business, and hence, opportunities to guide business strategy are plentiful.
• Guide team members on data science and analytics best practices to help them overcome bottlenecks and challenges.
• The role will be approximately 60% IC and 40% leading, and the ratios can vary based on need and fit.
• Develop Customer-360 Features that will be integrated into the Customer Data Platform (CDP) to enhance the single view of our customer

Requirements:

• The Role Advanced degree in an analytical field (e. g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands-on work experience in space 4-8 years of relevant experience in the space.
• Expertise in mining AI/ML opportunities from open-ended business problems and driving solution design/development while closely collaborating with engineering, product, and business teams.
• Strong understanding of advanced data mining techniques, curating, processing, and transforming data to produce sound datasets.
• Create great data stories with expertise in robust EDA and statistical inference.
• Experience in experiment design is a big plus, but one should understand the fundamentals of A/B testing.
• Strong understanding of the machine learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loops.
• Exposure to deep learning applications and tools like TensorFlow, Theano, Torch, and Caffe is a big plus.
• Experience with analytical programming languages, tools, and libraries (Python is a must) as well as shell scripting.
• Very proficient in SQL and other relational databases.
• Proficient in PySpark. Experience in using NoSQL databases.
• A candidate who is able to handle unstructured data with ease is preferred.
• Experience in working with AWS/Azure/GCP ecosystems.
• MLOps tool experience is a plus.
• Good understanding of programming best practices and building code artefacts for reuse.
• Should be comfortable with version control and collaborate comfortably in tools like Git.
• Ability to create frameworks that can perform model RCAs using analytical and interpretability tools.
• Should be able to peer review model documentation/code bases and find opportunities.
• Experience in end-to-end delivery of AI-driven solutions (deep learning and traditional data science projects) is a big plus.
• Strong communication, partnership, and teamwork skills Ability to work in an extremely fast-paced environment, meet deadlines, and perform at high standards with limited supervision.
• A self-starter who is looking to build from the ground up and contribute to the making of a potential big name in the space.
• Experience in banking and financial services is a plus.