Data Scientist, Amazon

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Data Science

Data Scientist role focused on building analytics and insights capabilities for Consumer Payments organization. This involves applying statistical and machine learning techniques to extract trends, identify anomalies, and develop scalable science solutions. The role requires collaboration with various stakeholders and a strong foundation in data querying and scripting languages.

What you'd actually do

  1. Working with technical and non-technical stakeholders across every step of science project life cycle.
  2. Design, develop, implement, test forecasting solutions for planning and goal setting exercises across various payment products and programs across CP organization.
  3. Apply statistical and machine learning techniques to extract meaningful trends and insights.
  4. Identifying real-time anomalies and early-detection mechanisms.
  5. Collaborate with Analysts, Business Intelligence Engineers and Product Managers to implement algorithms that exploit rich data sets for statistical analysis, and machine learning.

Skills

Required

  • 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
  • Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
  • Experience using complex modeling and analysis to inform key business decisions
  • Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
  • Can work proactively and independently, meet deadlines, and deliver on projects and tasks

Nice to have

  • Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
  • Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
  • Experience working with or evaluating AI systems
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Master's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or PhD
  • Knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker
  • Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
  • Experience in complex problem solving, and working in a tight schedule environment

What the JD emphasized

  • highly quantitative
  • experienced Data Scientist
  • build a new set of analytical experiences from the ground up
  • end-to-end ownership
  • successfully delivering results
  • Apply statistical and machine learning techniques
  • implement algorithms
  • build robust and scalable science solutions
  • state-of-the-art methods

Other signals

  • Develops analytics and insights
  • Build a new set of analytical experiences
  • Develop analytical solutions
  • Apply statistical and machine learning techniques
  • Identifying real-time anomalies
  • Implement algorithms
  • Build robust and scalable science solutions