Automation Associate (Python, Data Science)
Company Name:-
S&P Global
Job Location:-
Hyderabad, Telangana
Job Summary:-
The Role: Software Engineer / Data Analyst
The Location: Hyderabad
The Team: The Data Transformation team is responsible for driving key automation projects, machine learning based solutions and lean initiatives across S&P Global Market Intelligence.
We are responsible for creating, planning, and delivering transformational projects for the company using state of the art technologies and data science methods, developed either in house or in partnership with vendors.
We are transforming the way we are collecting the essential intelligence our clients need to do decision with conviction, delivering it faster and at scale while maintaining the highest quality standards.
Data Transformation has three major functions Cognitive Automation, RPA, and Data Management.
The Impact: This team has already delivered new breakthrough products and phenomenal efficiencies to the business.
In this role you will be working on the next generation of new products while enhancing existing ones and help to continue drive efficiency and reduce repetitive tasks.
Whats in it for you: We are a Fortune 500 company and recognized industry-leading provider of data and analytics: as such, we provide an unusually rich environment for software engineers and data scientists to make an impact and grow personally and professionally.
In addition to applying data science, you will have an opportunity to connect with leaders across S&P Global, our clients and partners; define new product opportunities; and be part of a lean, active, and professional team.
Responsibilities:
Develop and expand machine learning applications
Develop web-based GUIs and interactive dashboards
Develop restful APIs
Test, profile and enhance existing code base
Conduct data wrangling and analysis/modeling
Write technical documentation
Implement statistical analyses in R or python
Summarize data numerically and visually.
Understand and apply statistical and probabilistic tools
Carry out estimation and hypothesis testing in a variety of data situations
Perform linear and logistic regression analyses
Come to sound conclusions and avoid common pitfalls in data analyses
Work with common models for data, including the binomial and normal distributions
What Were L
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