[Jobs roundup] Does analysing data excite you? These openings may be the right choice

Big data is taking over the world today. This has lead to an increase in the importance of data analysts. Most organisations now look for data scientists/ analysts to crunch and simplify data.

Data science is all about analysing huge reams of data to derive useful insights for business. The data science domain demands a combination of mathematics, statistics, computer science, and information science to analyse and understand data.

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The data can then be used for multiple use cases such as to understand the demand or market, in decision making and predictive analysis, and for fraud detection and product development.

If you are someone who is data obsessed, smart, and analytical, these openings at some of the popular companies might be ideal for you.

Myntra

Experience needed: not specified

Myntra is looking for a data analyst who has a strong problem-solving ability. At Myntra, a data analyst will need to own projects- from conceptualisation to execution. The candidate will need to exhibit structured thinking, strong analytical skills, and process orientation. They are expected to understand and analyse data to drive business insights, and should have a strong process orientation and the ability to learn quickly. Their responsibilities also include monitoring and providing feedback loop during execution of various initiatives.

For more information, click here.

Apple

Experience needed: 8+ years

As a member of Apple's BI data analytics team, the candidate will be closely working with the engineering, product, and business operations teams within the advertising platforms group in meeting data reporting and analytical needs. In this role, the candidate will be responsible for developing and delivering dashboards, actionable insightsm and reports in support of rapid decision-making. They will be also required to write optimised SQL scripts to query and prepare data sets for analytical needs. 

Apart from this, the candidate needs to understand the trends in relationships between raw events and key business metrics. They should recommend innovative ways of analysing data and come up with the right set of measures for overall product health.

For more information, click here.

Amazon

Experience needed: 1+ years

As a data analyst at Amazon, the candidate will be responsible for creating and automating reporting processes for service providers, consolidating service requests across channels, and streamlining operations for provider performance and service fulfilment. They will have to work closely with product management to design, implement, and deploy applications that impact the Amazon seller services business. The candidate will also be responsible for creating and executing appropriate quality plans, project plans, test strategies and processes for development activities with business and project management efforts.

For more information, click here.

PayPal

Experience needed: 1-2 years

The company is seeking a data analyst to develop its risk strategy within the next-generation platforms and strategic partners portfolio. Each analyst on this team will have full ownership of a portfolio of merchants and will be responsible for end-to-end management of loss and decline rates. Their day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure delivery of the best possible customer experience while meeting loss rate targets.

For more information, click here.

HP

Experience needed: 4-6 years

The responsibilities of a data analyst at HP include designing and establishing secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. The candidate is required to analyse the design and determine the coding, programming, and integration activities required, based on general objectives and knowledge of overall architecture of product or solution. They will also be responsible for writing and executing complete testing plans, protocols, and documentation for assigned portion of data system or component; identifying, debuging and creating solutions for issues with code and integration into data system architecture.

For more information, click here.