SplashLearn - Business Analyst

Primary Skills -:
1. Your primary focus will be to oversee the collection, analysis, and interpretation of product data, ensuring data integrity and actionable insights. You will be a key partner to the product. Deep diving into data to measure the performance of newly launched features and making data backed recommendations to improve product performance.
2. Prepare and present comprehensive reports, dashboards, and visualizations to communicate key findings, trends, and recommendations to stakeholders.
3. Proficiency in data analysis tools and programming languages such as Python (good to have), R (good to have), SQL (mandatory), and familiarity with data visualization tools (e.g., Tableau, Power BI).
4. Experience with AB test analysis. Deep diving into AB test to establish correlation and causation.
5. Experience with statistical analysis.
6. Drive the development of predictive models and algorithms to identify anomalies, trends and product levers (good to have).
7. SQL - Should have expertise on building complex and highly optimized SQL queries.

8. Data modeling/ \ETL - Strong logical & analytical concepts in databases, schemas, dimensional modeling enabling fast and accurate access of metrics and its drill down.
9. BI Tools - Experience of working with BI tools such as Looker, Power BI, Tableau.
10. Automation - Strong rigor in automating repetitive tasks and processes.
11. Ability to multitask and work on a diverse range of requirements.
12. Ability to adapt to and learn new tools/ techniques (Hevo, Pentaho, Fivetran, Airflow etc.) quickly.
13. Attention to detail and strong data orientation.
Good to have -:

1. Basic understanding of web analytics tools such as google analytics, mixpanel etc.
2. Basic understanding of scripting languages (R, Python, etc.)
3. Basic understanding of statistical concepts such as application of mean, median, percentile, variance, standard deviation, normal distribution, p value, confusion matrix etc.
Responsibilities -:
4. Design and develop complex data queries to move and transform data from operational data sources to analytical databases.
5. Act as a bridge between your team and the data engineering teams, you will ensure that proper table structures / solutions are built to draw insights and it's fully validated.
6. Capture reporting requirements and design tables, metrics, reports and dashboards that enable stakeholders to gather understanding on activation rate, conversion rate, content consumption, engagement and retention.
7. Documentation - Ensure meticulous documentation of processes, meta data, query logic, and results.