Data Scientist

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.

Skills Required

• 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, Google 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.

Desired Skills (Business)

• 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.