S&P Global Recruitment Drive; Hiring Data Scientist Apprentice – Apply Now

S&P Global is currently seeking a Data Scientist Apprentice to join their team. This is a unique opportunity for individuals eager to kickstart their careers in data science within a globally recognized financial information company. As an apprentice, you'll gain hands-on experience working alongside seasoned data scientists, learning to leverage advanced analytical techniques to extract valuable insights from complex datasets. This role offers a chance to develop essential skills in data cleaning, manipulation, modeling, and visualization, while contributing to critical business decisions at S&P Global.

Name of the Organization: S&P Global

Requisition ID: 307120

Positions: Apprentice - Data Scientist

Location: Hyderabad & Bangalore

Salary: As per company Norms

Required Skills & Qualifications:

• Graduate
• Good Python skills in order to maintain and create Python files for data analysis.
• Competency with Excel in order to store and present data analysis.
• Knowledge of SQL (PostgreSQL will be the platform) in order to write basic queries.
• Good data analysis skills

Job Description:

As part of Content Vortex, we are leveraging Gen AI to extract data from drilling completion and permit documents. Every state that has drilling activity has their own unique sets of documents. Currently it is mostly a manual process to extract the data from the documents into the database.

• Every US state that has drilling activity has their own unique sets of documents. Currently it is mostly a manual process to extract the data from the documents into the database. Using Gen AI will help automate the data extraction.
• The role offers work on Gen AI related tasks such as prompt engineering, using Langchain to connect to the LLM’s and run the prompts, and quality control with respect to the accuracy of the data extracted.
• This role is focused on helping the data scientists with the post extraction data analysis in order to quantify the effectiveness of the prompts and in order to decide if further prompt engineering needs to take place.
• Use existing / create Python files to automate the data analysis of the extracted data in order to create a ground truth.
• Maintain all data analysis cleanly in Excel spreadsheets.
• Help the data scientists with any data analysis or other data science as the need arises.

 

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