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.
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Job Description & Responsibilities:-
- 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.
- Document new methodologies and code.
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