Senior Manager - Marketing Analytics - KPO

Sr Manager- Marketing Analytics

Years of Experience: 8-12 years

Location: Pune

Brief about position:

- The Manager has responsibility for day-to-day management of data related to Omnichannel Customer Analytics who will use a variety of data sources including but not limited to, customer, content, channel and web to develop analyses to drive actionable insights and help make sound business decisions.

- Support analytics leaders to design advanced innovative analytics methodologies, improve analytics operational efficiency, explore new data sources and new ways of developing advanced analytics solutions and be involved into ad-hoc omnichannel analytics projects for the digital analytics and innovation team and will be one of key members to drive the success of digital marketing globally for the client.

Primary Responsibility:

- Understand business requirements and work as an expert to lead omnichannel customer analytics projects

- Work with other analysts to design analytics methodologies and conduct data discoveries to provide best-in-class analytics solutions; provide mentorship to junior analysts.

- Assess digital promotion or tactic performance, analyze customer behavior and customer journey, deep dive vendors' analytics and optimization capabilities, conduct content analysis or modelling to optimize customer experience

- Design experiments and develop analyses include but not limited to optimal targeting timing, frequency, location, content etc.

- Create and present compelling, easy-to-understand data visualization and data driven insights for analytics leaders

- Responsible for developing and maintaining extensive analytics deliverables and meet quality standards, timeliness, compliance, and excellent user experience

- Work with other analytics groups such as web, targeting, ROI on cross-functional initiatives in providing relevant data to generate customer-focused viewpoints

- Conduct extensive data mining and investigation to understand organizational database, various data sources, identify data gaps and provide data requirements to different functional areas including MDSI (Master Data Strategy & Integration), reporting, tagging, and various project managers to expand digital data capture, enhance digital data quality and improve the data usage i.e., 3rd party data assets, email data, content data, Rx and offline promotion data

- Identify when an ongoing HCP omnichannel customer analytical request should be migrated to the reporting and BI solutions team for automation; clearly articulate reporting requirements and facilitate automation needs; responsible for documentation and query standardization, etc.

- Build communicates standards, benchmarks, and processes for the daily execution of data stewardship tasks, use of common methods tools. Collaborate closely with the Data Champions, DQ Experts and Data Solution designers to ensure alignment between central DQ activities and the stewardship community

- Collaborate closely with the Functional Decision Owners, Data Champions, Data Maintainers, Stewards IT organization to calibrate, discuss and resolve Data Governance and Quality issues

- Own, build and maintain the metadata, data quality parameters, data lineage, important metric reports and workflows to ensure that data is governed, consistent, reliable, and easily accessible.

- Review and approve data exceptions for the data built by Data Maintenance team. Crafts an effective data community with a distinct identity, to facilitate shared learning between Business Users and Stewards and to promote active Data Governance through the Data Governance team.

Required Experience:

- 8+ years of professional experience doing quantitative analysis at the digital campaign, customer, channel, and content level

- Hands on coding experience in Python, R, and SQL are required

- Strong problem solving, business analysis and quantitative skills

- Working knowledge of statistical and data science principles to enable adequate understanding of design of experiments, algorithm models (linear or logistic regression, cluster analysis, decision tree methods, propensity score matching etc.), the appropriate application of different models, and effective communication to business audiences

- Good understanding of CRM database, web tagging, data warehousing, cloud environment (AWS), data architecture and ETL

- Proficient in manipulating and analyzing complex data set for both planned and ad hoc analysis

- Detail oriented and commitment to producing high-quality work and maximizing resources, while meeting deadlines

- Ability to present work logically, clearly and improve customer experience and engagement

- Digital media or customer analytics experience is a plus