Consultant - Analytics - KPO (3-5 yrs)

Technical and domain expertise:

Expertise in SQL & Python/R with Statistical techniques and reporting

Role:

The team member is expected to work directly with the client in a fast-paced working environment to address their day-to-day analytics needs.

The indicative areas of work could be:

- User Analytics - Understanding user behavior in the app, feature adoption, understanding retention & churn drivers etc., transaction behavior across features, offer & scratch card redemption, impact of email and notifications

- Marketing measurement - Evaluating effectiveness of marketing campaigns through channels like ATL & performance media

- Product analytics

Responsibilities:

Client management:

- Be able to lead the conversations with the client and develop deep understanding of the nature of work to share new ideas and opportunity segments

- The candidate is required to bring in consulting expertise and work closely with the client to identify opportunities for growth and scale the engagement

- Communicate with the clients and understand their business needs

Technical:

- Work with large, complex data sets to solve difficult, non-routine analysis problems, applying advanced analytical methods as needed

- Build data pipelines, and dashboards for marketers to self-serve data needs; enable automated tracking of marketing campaigns

- Harmonize data as required and setup models according to the business logic defined

- Use statistical tools to identify and evaluate the relationships between data fields, analyze output and determine the next action

- Project management: Lead at least one client engagement independently. Execute end to end client engagements. Ensure regular client updates & meetings, stakeholder management, any failure or risk analysis of the project, data sources, tracking execution & success metrics is done effectively & efficiently.

Qualifications & Experience:

- Hands on experience with databases, SQL coding across standard commercial databases (e.g., Teradata, MySQL), and statistics tools (e.g., R / Python).

- Hands on experience with quantitative analysis/modeling (e.g., scenario-based, sensitivity analyses, statistical techniques) and reporting

- Advanced knowledge of SQL is a must

- Good problem solving & insight generation skills

- Excellent communication skills with technical and non-technical stakeholder