Job
Description
Roles & Responsibilities: Develop insights to identify opportunities and drive product strategies. Gain insight into customer use of current products, untapped opportunities and buyer personas. Partner with product/business teams to define goals and identify key metrics for existing features and new releases Build automated dashboards and reports, craft analyses and tell stories with data to help our teams make better decisions Drive awareness and understanding of key metrics and experiment results Monitor the performance of new features and recommend iterations based on your findings Deep dive into assessment of key drivers for KPIs by drawing relevant business hypothesis and quantify the impact of these drivers on the relevant KPI Execute deep & complex quantitative analyses that translates data into actionable insights Drive data driven decision making through the stakeholders. Work with complex, non-routine analytical problems, applying advanced methods when needed. Influence data-driven decisions across the business spectrum - product/data science /engineering/finance / partnerships - through end-to-end ownership of projects Collaborate and coordinate across functions to dissect business, product, growth, acquisition, retention, and operational metrics. Required skills & Qualifications: Bachelors degree in Computer Science, Engineering or related field from top tier (IIT/IIIT/NIT/BITS) and work experience with 1-4 years experience in a data analysis related profile for an internet company The ability to clearly and effectively communicate the results of complex analyses Is detail oriented, with a strong passion for analytics and problem solving Is excited to work in a fast paced environment, is comfortable with making decisions in ambiguity, and has a strong bias for action. Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems, api frameworks, storage systems on premises and cloud-based data sources along with strong SQL skills. Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units. Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc. Experience with Excel, Word, and PowerPoint. Strong background in statistical modeling and experience with statistical tools such R, Python, Spark, SAS or SPSS. Able to self-manage your priorities and deliverables while working in a fast-paced, startup environment Have hands-on experience with visualization tools (Tableau, PowerBI, Qlikview, D3.Js) Any exposure to the Fintech industry, preferably digital lending background, is a plus.
