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Data Scientist at PayPal

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

18 Mar, 26

Salary

0.0

Posted On

18 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Statistical Analysis, SQL, SAS, Hadoop, Python, R, Data Quality, Data Integrity, Predictive Modelling, Data Mining, Business Judgment, Analytical Thinking, Reporting Tools, NLP, Time Series Forecasting

Industry

Software Development

Description

Develop and implement data science models and algorithms. Analyze and interpret complex data sets. Ensure data quality and integrity. Collaborate with stakeholders to understand data requirements. Optimize data processes for efficiency and performance. Perform advanced statistical analysis and reporting. Minimum of 2 years of relevant work experience and a Bachelor's degree or equivalent experience. Solid technical / data-mining skills and ability to work with large volumes of data; extract and manipulate large datasets using common tools such as SQL, SAS, Hadoop, or other programming/scripting languages (Python, R, etc.) to translate data into business decisions/results Be data-driven and outcome-focused Must have good business judgment with demonstrated ability to think creatively and strategically Must be an intuitive, organized analytical thinker, with the ability to perform detailed analysis Takes personal ownership; Self-starter; Ability to drive projects with minimal guidance and focus on high impact work Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Engineering or related field with 2-3 years' experience, or Master's degree with 1-2 years' experience in risk management, data science and/or loss forecasting, in the payments space or banking/finance services industry would be particularly desirable. Proficiency using SQL and querying relational databases Experience in at least one statistical programming language (SAS, R, Python) Familiarity with reporting tools (Tableau, Power BI or Qlik) is highly desired. Experience in predictive modelling techniques such as Regression, Classification, Time series forecasting, NLP, etc. Experience with structuring analyses to solve business problems using data and analytics tools and techniques

Responsibilities

Develop and implement data science models and algorithms while analyzing and interpreting complex data sets. Collaborate with stakeholders to optimize data processes for efficiency and performance.