Role:

 A Data Analyst is responsible for understanding and deriving insights from the data collected by the company. He would be responsible for maintaining the data and building models from scratch using this data and also tuning and improving existing models as per business requirements.

What you will do in this role

• The Data Analyst will be responsible for understanding and deriving insights from the data collected by the company.


• They would be responsible for maintaining the data and for performing extensive analysis from data to derive actionable insights as per business requirements.


• They would have to quantify the impact of proposed initiatives, identify causations and correlations and differentiate between them.


• They would have to perform clustering to segment customers or build decision trees to analyze churn or forecast using regression models.


• They would have to assess the results of A/B experiments.


• They would have to identify and build metrics and reports as and when required and automate these processes as expected.


• The candidate is expected to be able to analyze large amounts of data and should have the ability to work with an appropriate data warehouse solution to do so.

What you should have

• Degree in statistics, engineering or a related discipline and a passion or expertise in data and statistical analysis.


• Experience working in areas such as data warehousing, databases, data visualization, statistics, data analysis, A/B Experiments, reporting, basic machine learning and modelling.


• Comfortable working with massive unstructured data sets.


• Good working knowledge of technologies such as SQL, Excel, Google Analytics, Tableau/Qlik and R or Python.


• Expertise in deriving insights from large amounts of data is mandatory


• Expertise in customer segmentation, user profiling, and churn analysis is required.


• Ability to work with large data sets and to interpret them statistically is expected.


• Strong problem solving skills is required.


• Expertise with SQL and MS Excel is mandatory.


• Detailed understanding of statistical techniques is expected.

Brownie Points

• Experience in working with big data platforms such as Hadoop, Spark, Hive, Pig will be useful.


• Exposure to BI tools such as Looker or Tableau will be useful.


• Experience using machine learning algorithms, data analytics strong algorithmic thinking and good programming skills will be useful


• Proficiency in R or Python will be useful


• Experience working on analytics and tracking tools such as Google Analytics will be preferred