Nielsen is hiring candidates for the role of Data Scientist for the Bangalore, Karnataka, India location. The complete details about Nielsen Off Campus Recruitment are as follows.
Company Name:- Nielsen
Job Position:- Data Scientist
Job Location:- Bangalore, Karnataka, India
Salary Package:- As per Company Standards
Job Type:- Full-Time – Hybrid
Required Qualifications and Experience:-
0-3 years work experience
Proficiency in Python, Spark, SQL Degree in data science, statistics, engineering, applied mathematics, operations research, information sciences, or another biological/physical science.
Strength in code documentation
Proficiency in Git and code versioning tools (Gitlab)
Proficiency in Atlassian Suite such as JIRA and Confluence.
Familiarity with cloud computing (AWS, Goolge Cloud preferred)Knowledge of statistics and machine learning
Ability to manipulate, analyze, and interpret large datasets
Knowledge of dashboarding and visualization tools like Spotfire/Tableau
Business Skills:
Excellent oral and written communication
Self-motivation and an ability to handle multiple competing priorities in a fast-paced environment
Strong interpersonal skills and the ability to develop effective relationships with other team members, including remotely.
Build measurement and planning solutions for publishers, advertisers, and agencies.
Support reproducible data science projects end-to-end
Deploy and maintain data pipelines and models in a production environment
Work with cross-functional teams to productionize, validate, and optimize methodologies
Communicate methodology and research findings to varying audiences
Support research on methodology changes to cross-platform audience measurement.
The primary research areas include trend analyses, imputing missing data, representation/ sampling, bias reduction, indirect estimation, data integration, and automation.
Continuous support and development of new projects by exploring the data – Variable Identification, cleaning the data , applying dimension reduction techniques, calculating distances and integrating the surveys.
And also using output evaluation techniques in order to make sure of the accuracy.
Address quality escapes and fix issues in production code.
