As a Senior Data Analyst, you will play a pivotal role in extracting actionable insights from data, providing valuable recommendations, and contributing to the strategic decision-making process. You will work closely with cross-functional teams to analyze complex datasets, develop data-driven solutions, and enhance overall business performance.
Key Responsibilities:
- Mine, and analyze granular hit/event level web, product, sales, and digital marketing data.
- Build Tableau dashboards to support product stakeholders.
- Build Tableau data sources that can allow for self-serve usage of product and web data.
- Build conversion funnels across multiple product lines to help product teams understand the complete customer journey.
- Develop customer segmentation models and activation testing plans
- Work with data engineers to improve and maintain the customer360 and API data models by defining new feature requirements, making improvements to taxonomy, and identifying bug fixes.
- Work with cross-functional teams (BI Enterprise Data Warehouse, Salesforce MOPS, IT, Product teams) to gather and refine requirements for metrics and dashboards needed by product stakeholders.
- Develop a good understanding of the business’s model, objectives, issues, and challenges by interacting and collaborating with leaders and stakeholders.
Key Skills:
- Experience using Tableau Desktop/Creator, Adobe Analytics, Amplitude
- Advanced SQL knowledge
- Experience with cookie-level advertising platform data (Google, Bing, Epsilon, LinkedIn, Facebook etc.) and measuring demand generation KPIs (ROAS, CTRs, Impressions, MTA Attribution, MMM).
- Experience with cookie-level web/product data and KPIs like usage, conversion funnels, bounce rates, unique visitors, sessions, hits/events, pathing and journey optimization.
- Experience with designing A/B/Multivariate/Lift testing and measurement for both digital and offline demand generation channels.
- Experience gathering and refining requirements from business stakeholders.
- Experience communicating dashboards and findings to both technical and non-technical audiences.
- Experience using Python, SciKit, SQL, Snowflake, hit-level Adobe Analytics data, product usage data, Jupyter Notebooks, Amazon SageMaker, Airflow, Github
- Proficiency with data mining, mathematics, and statistical analysis techniques.
- Experience with predictive modeling techniques, unsupervised, supervised, reinforcement, causal inference machine learning techniques.
- Experience with the following ML steps: data prep, choosing model, feature creation and selection, training, evaluation, parameter tuning, making predictions
Education and Experience:
- B Tech or B. E. (Computer Science / Information Technology)
- 5+ years experience as a Data Analyst or similar roles
Analytical and Personal skills:
- Must have good logical reasoning and analytical skills
- Good Communication skills in English – both written and verbal
- Demonstrate Ownership and Accountability of their work
- Attention to details
