Data Analyst
Company Name:-
Evive
Job Location:-
Bengaluru, Karnataka
Job Summary:-
Data AnalystEvive people are game-changers.
Evive was founded by two people who wanted to challenge the status quo.
and did. Since 2007, that spirit has defined our culture.
The work we do is redefining how people use their employee benefits, with SaaS-based services that help people to improve their lives and Fortune 1000 enterprises to optimize their benefits investments.
We strive every day for the ideal of #benefitslove.
Are you one of us?We’re looking for a thorough Data Analyst.
Is it you?
The goal is to find and extract the hidden patterns in any data by application of appropriate mathematical methods/algorithms.
Constructive criticism on applications; working closely with Business/Development team to provide suggestions about how to make a product better and user-specific.
Key Responsibilities
Knowing the complete working of an application, the business goal, all of different data sources/sink, and any transformation that data undergoes[complete data flow].
Working with products PM/PO to understand the product Success Metrics/KPI, and come up with possible analysis solutions that help them to measure the product usage and make product decisions.
Working with the product team, in providing the data requirement for the product and also make sure all the data required for the analysis is getting stored.
Providing any adhoc analytical solutions as per the product team’s requirement.
Periodic post production analysis of the product usage.
Creating and building different data Exploration and Transformations pipelines, as raw data needs to be transformed and explored for any analysis.
Do different statistical tests to understand and evaluate the results, Draw useful insights, Know how to do presentations; creation of analytical reports/dashboards from the analysis.
Based on the analysis results, review/recommend/suggest any changes in product by working with the Business team.
Building basic ML models as part of analysis.
Skill Requirements
Experience and proficiency in core statistics, SQL and No-SQL, R, Python, Elastic search or other data analytics tools, both in concept wise and the application wise.
Experience and proficiency in Linear ML techniques and algorithms (regression, classification, clustering)
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