Wenger & Watson | Analytics Consultant
8 hours ago
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:
o 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
o The candidate is required to bring in consulting expertise and work closely with the
client to identify opportunities for growth and scale the engagement
o Communicate with the clients and understand their business needs
• Technical:
o Work with large, complex data sets to solve difficult, non-routine analysis problems,
applying advanced analytical methods as needed
o Build data pipelines, and dashboards for marketers to self-serve data needs; enable
automated tracking of marketing campaigns
o Harmonize data as required and setup models according to the business logic defined
o 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 stakeholders
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