Manager /Sr. Manager - Machine Learning
Noida, Uttar Pradesh
Analytics – Paytm Money /
On-roll /
Hybrid
Evangelize and demonstrate value and impact of analytics for informed business decision making by developing and deploying analytical solutions and providing data driven insights to business stakeholders to understand and solve for various lending business nuances.
Expectations/ Requirements:
8+ years of exposure into Data Science/Machine Learning Bachelor's or master's degree in computer science, data science, or a related field.
Build and strengthen relationships with functional leaders in sales, product, growth, risk and collections by identifying areas where analytics could help solve existing problems or strengthen business operations
Machine learning model building experts are required who have worked specifically on Machine Learning techniques like Linear/Logistic regression, XG Boost, Random Forest, etc Apply problem solving frameworks to break the complex business problems faced by the BUs and organization in smaller more manageable problems and translate the business problem in to data and analytics problem
Identify various business opportunities and apply analytics to optimize conversions and risk
Generate actionable recommendations based on huge platform data and communicate the insights generated by the teams
Share reports and dashboards with business stakeholders to empower them to make data driven decisions
Manage transformation projects that help to improve top line or bottom line through an analytical solution
Be the champion of data and insight led decision making in the organization and drive change management efforts to bring stakeholders on board
Manage a team of data scientists/Machine Learning engineers to deliver analytical solutions and data driven insights to the business stakeholders
Superpowers/ Skills that will help you succeed in this role
High level of drive, initiative and self-motivation
Skills Mandatory- Python, SQL, Machine learning techniques
Ability to take internal and external stakeholders along
Strong people management exposure
