Responsibilities :
Business Analyst would be responsible for working closely with the Business Teams and helping them in making data driven decisions. This would require cross-communication between the Business Team, Product Team & Data Engineering as well. Apart from solving the business problem at hand, a business analyst would also be responsible for sharing insights and learning basis the data exploration/mining and convert these into clear action points and ensure that the same are being worked upon
Getting business requirements from the respective Business Teams, identifying the
underlying business case and building a generalized solution
Extracting & Exploring the data from database and other sources that may exist,
cleaning the data for any issues/missing values also needs to be owned upon
Converting the cleaned data into actionable insights and sharing the same with relevant
Audience
Automation of data problems/solutions that occur recursively
Flagging to Data Engineering in case of data sanity issues are to be seen
Ensure that the action insights shared with the business teams are worked upon
Ensure new business requirements are thoroughly vetted and signed off
Knowledge sharing within the team and outside if required
What are we looking for ?
1 to 6 years of work experience in the relevant field, preferably in a consumer facing company
Proficient in MySQL & PostgreSQL, ability to handle complex/inner queries
Hands-on with Microsoft Excel (basic data cleaning, pivoting and data exploration)
Must have worked on any one Data Visualization Tool (Tableau, Qlikview, Qliksense, Spotfire,Power BI etc)
Basic automation skills using Google Sheets or Microsoft Excel are expected
Working knowledge on handling data in R/Python is a plus
Communication skills to get the business requirements and give out the final insights
Data Inquisitiveness
PharmEasy was founded in 2015 with the sole purpose to make healthcare easily available, accessible and affordable to all through the extensive use of new-age cutting-edge technology. Today, we are one of India's largest healthcare aggregators connecting lakhs of patients to licensed pharmacies & diagnostic centres online for all their medical needs. We are particularly catering to the chronic-care segment, and offer a range of services including medicine delivery, tele-consultation, sample collection for diagnostic tests as well as subscription-based services for all these categories.
Our highly efficient and technology led Consumer and Supply-chain platforms ensure that medicines are delivered from a licensed pharmacy within six hours of the validation of prescriptions submitted by our customers. And such customer promises are improving with the increasing scale of our business, and continuous product innovation.
By extensively leveraging the latest in hardware and software technology, we are also committed to eradicate fake medicines from the Pharma ecosystem that contribute to roughly 30% of drug volumes in India. Our product innovations have allowed for complete data transparency in the entire Pharma supply-chain to empower even the end-users to validate the authenticity and genuineness of the medicines for every medicine sold, using constructs such as unique barcoding of information like expiry dates, origination of drugs etc.
With our scalable technology and processes, we are now reliably delivering healthcare services and medicines to every single pin code in the country.
Analytics @ Pharmeasy:
Pharmeasy wants to enable data driven decision-making for achieving the core business objective of the company to make healthcare accessible & affordable to everyone. This would essentially require rigorous efforts being put into all domains of analytics from data collection to data extraction to data cleaning to data wrangling to descriptive analytics and eventually drawing business insights and communicate the same to the relevant business teams. We want to make analytics an integral part of every decision making at Pharmeasy because in today’s world subjectivity is something that is limited to academia and data can answer most of the questions.
