Overview:
This role would be part of Niro Money, Data and Analytics team and is essential for translating data into actionable insights that improve marketing ROI, business growth and enhance customer experience for different financial products e.g. personal loan, home loan, credit card, insurance etc. The ideal candidate should have a strong background in data analytics and the ability to deliver strategic recommendations for key stakeholders and business heads.
Key Responsibilities:
- Lead, mentor and develop a high performing team of data analyst and data scientists focus on building decision science model/segmentation to predictive customer behaviours and developing data driven strategies to optimize marketing ROI for different kind of financial products (personal loan, credit card etc).
- Partner with Partnership & Marketing team and run marketing experiments to improve funnel conversion.
- Measure effectiveness of marketing campaigns & experiments, clearly called out what's working vs what's not working and recommend necessary changes including customer journey related product changes.
- Cultivate a culture of collaboration, innovation and data driven decision marketing across multiple teams within Niro
- Effectively manage multiple analytics projects simultaneously, prioritized based on potential business impacts. Ensure timely and accurate project completion. Project planning and monitoring, promptly address challenges to keep projects on tracks
- Partner with Data engineering, technology and product teams to develop and implement data capabilities to run marketing experiments and deliver actionable insights at scale
Skills and Qualifications:
- Master's degree in statistics, mathematics, data science, economics, or BTech in computer science or engineering,
- 5+ years of hands-on experience in decision science analytics and building data drive strategies preferably in financial service industry
- 2+ years of Experience in managing and leading a team of data analyst and data scientists
- 2+ years of hands-on experience in statistical model development in financial service industries, leveraging logistic regression/Gradient boosting algorithms using python packages e.g. Scikit learn, XGBoost, Stats models or decision tree tools.
- 2+ years of hands-on experience in SQL, Python
- A proven track record of decision making and problem solving based on analytics. conceptual thinking skills must be complemented by a strong quantitative orientation, as a large part of the business is based on rigorous analytic marketing & partnership channel optimization
- Experience with Snowflake, AWS Athena/S3, Redshift ,BI Tools AWS Quicksight is a plus
- Strong analytical mindset and the ability to evaluate complex scenarios and make data-driven decisions.
- Be creative and curious, willingness to learn new tools and techniques.
- Data-oriented personality, ability to work with high level objectives and formalising approaches and solutions.
- Excellent communication and interpersonal skills to effectively collaborate with diverse stakeholders.
