Job Summary: 

• Lead the analytics team for Retail Lending, Rural Lending, Cards and Payments Business
• Co-own business number targets for analytics-driven business outcomes
• Drive business insights based on data and implement them in systems
• Create a competitive advantage for business through the use of analytics
• Work with top-end vendors/fintech to bring the best solutions in the lending business
• Foster a culture of analytic decision-making across the business
• Drive business value through more optimized data-based decision making
• Drive business growth through the use of data and insights for the retail lending business units
• Lead a large team of business analysts/data scientists
• Create new-age solutions through usage and implement ML solutions in a big data environment
• Create and maintain the foundational data infrastructure

Skills on Resume: 

• Leadership (Soft Skills)  
• Analytics (Hard Skills)  
• Business Strategy (Soft Skills)  
• Data-driven Decision Making (Hard Skills)  
• Collaboration (Soft Skills)  
• Machine Learning (Hard Skills)  
• Data Infrastructure Management (Hard Skills)  
• Team Management (Soft Skills) 

Job Summary: 

• Perform simultaneous large, complex, and business-critical analyses/abstract problems that serve major parts of the business.
• Discover insights using statistics, data mining, and visualization techniques
• Develop scalable models and tools that speed up both decision-making and accuracy for the team.
• Be a key influencer in strategy and contribute significantly to overall planning.
• Navigate discordant views, find the best way forward, and influence stakeholders around a solution.
• Define, develop, and maintain critical business reports reviewed at a defined cadence.
• Help to automate processes by developing deep-dive tools, UIs, metrics, and dashboards to communicate insights to the business teams
• Analyze historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations
• Collaborate with the data engineering team to implement analytics systems and data structures to support large-scale data analysis and the delivery of ML and econometric models
• Understand the broad range of Amazon’s data resources, which to use, how, and when
• Collaborate effectively with internal end-users and cross-functional teams to solve problems and implement new solutions.

Skills on Resume: 

• Problem Solving (Soft Skills)  
• Statistics (Hard Skills)  
• Data Mining (Hard Skills)  
• Visualization (Hard Skills)  
• Model Development (Hard Skills)  
• Stakeholder Influence (Soft Skills)  
• Automation (Hard Skills)  
• Collaboration (Soft Skills)  

Job Summary: 

• Work with the Senior Management team to create data solutions for new business pitches.
• Create solutions in attribution and bidding solutions using lifetime value and CRM data to produce insights.
• Create audience plans that cover all elements of a user journey, as well as creating Lifetime Value bidding models to optimize paid media.
• Create and champion best practices in data, with the use of Cloud and Lifetime value modeling in key accounts
• Collaborate with clients and consult on data usage across their portfolio
• Cross-sell data projects to clients and act as a subject matter expert within Digital Data for the business.
• Influence the Data Engineering and GMP teams to adopt a uniform approach to Data.
• Manage, mentor, and coach the current team, and scale this team over the coming years.
• Set mid and long-term machine learning strategy
• Explain the possibilities of using state-of-the-art analytics and ML processes in the company and acquire lighthouse projects
• Establish solutions and manage the company initiatives, analytical processes

Skills on Resume: 

• Data Solutions (Hard Skills)  
• Attribution Modeling (Hard Skills)  
• Audience Planning (Hard Skills)  
• Lifetime Value Modeling (Hard Skills)  
• Client Collaboration (Soft Skills)  
• Cross-selling (Soft Skills)  
• Leadership (Soft Skills)  
• Machine Learning Strategy (Hard Skills)  

Job Summary: 

• Implement technology ways of working in the team, including defining intake, prioritization, and continuous improvement processes.
• Build a complete understanding of the KPIs of platform business, comprising internal, customer, and partner views. 
• Showcase platform performance in the organization through roadshows, sharing of analysis, and direct engagement with stakeholders.
• Define a product roadmap for reporting, engage with data backend teams, and become an influencer of the related product roadmaps. 
• Define performance KPIs in close collaboration with partner-facing direct portal teams.
• Strongly believe in putting people first and investing time in developing and coaching the team
• Work with other teams or external vendors to create data marts, document data processes, identify data/intelligence gaps, and address them on an ongoing basis
• Data-driven decisions on resource allocation, productivity metrics, and creating scorecards to drive resource management decisions
• Granular understanding of all line items of cost and profitability for the business, thereby driving optimization efforts
• Ensure that the valuation framework (lifetime value) is created and is being used for all retail lending, cards, and payments products in key optimization decisions
• Actively involved in the major decision-making process with all key business heads

Skills on Resume: 

• Technology Implementation (Hard Skills)  
• KPI Analysis (Hard Skills)  
• Stakeholder Engagement (Soft Skills)  
• Product Roadmap Development (Hard Skills)  
• Performance Optimization (Hard Skills)  
• Team Development (Soft Skills)  
• Data Mart Creation (Hard Skills)  
• Resource Allocation (Hard Skills)  

Job Summary: 

• Lead, grow, and develop an analytics team responsible for driving actionable insights for the Customer Experience team. 
• Responsible for web and merchandising analytics (including page effectiveness, product placement optimization, site friction points, traffic and conversion metrics, personalization, etc.), customer lifetime value, pricing, and promotional optimization.
• Utilize big data analytics and data science modeling techniques to build machine learning models necessary to uncover opportunities associated with site optimization, customer journey, and personalization to maximize customer lifetime value.
• Create a test and learn culture to unlock value and drive continuous improvement within the customer experience.
• Work with the internal IT stakeholders to identify, develop, or enhance the applications portfolio that supports E-Commerce operational excellence. 
• Ensure the Analytics team has the necessary data and tools to understand site optimization and the customer journey from site entrance to order placement. 
• Collaborate with IT, including understanding all the disparate data sources, identifying data gaps, and setting the priority roadmap for migrating all relevant operational data to a single reporting platform of record.
• Develop strategies and provide direction for the development and application of Business Intelligence tools that provide robust KPI's and drill-down capabilities to unlock site optimization opportunities.
• Deal with ambiguity, a go-getter who figures things out, and can turn insights into executable strategies that improve financial results.
• Interface and drive engagement with a wide variety of internal and external stakeholders.
• Synthesize results tailored for the intended audience to best answer questions they have and address possible concerns.

Skills on Resume: 

• Technology Implementation (Hard Skills)  
• KPI Analysis (Hard Skills)  
• Stakeholder Engagement (Soft Skills)  
• Product Roadmap Development (Hard Skills)  
• Performance Optimization (Hard Skills)  
• Team Development (Soft Skills)  
• Data Mart Creation (Hard Skills)  
• Resource Allocation (Hard Skills)