Job description
 
As a part of Big Data Analytics/AI-ML team you will play the leadership role in defining and developing high performance Big Data ETL data pipe. You will work with domain experts to identify the most efficient way to collect and process batch/time series data to derive data insight. You will work with Machine Learning/Deep Learning engineers to develop models that can help in Predictive and Prescriptive data analytics.
 
You will also play critical role to establishing a process of causal inference which can help Chip Design/Verification Teams in making data driven decisions.
 
What You'll Need
  • Knowledge of underlying mathematical foundations of statistics, machine learning, and analytics.
  • Experience with exploratory data analysis, statistical analysis and Hypotheses testing, and model development.
  • Fluency in SQL and Spark to write efficient codes at scale with large datasets
  • Experience using Python Programming, writing applications that scale with large data sets.
  • Experience in building and evaluating machine learning models
  • Proven experience of 2+years in the relevant field.
    MS or Bachelors degree in Statistics,  Machine Learning, Operations Research, Computer Science or other quantitative fields.

 
What You'll Do

  • Drive clarity and solve ambiguous, challenging problems using data-driven approaches. Propose and own data analysis (including modelling, coding, analytics, and experimentation) to derive data insight and facilitate decisions.
  • Develop creative solutions and build prototypes to problems using algorithms based on machine learning, statistics, and optimisation
  • Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative impact and extract trends

 
Basic Qualifications

  • MS or Bachelors degree in, Statistics, Machine Learning, Operations Research, Computer Science or other quantitative fields. (If M.S./M.Tech. degree, a minimum of 2+ years of industry experience required and if Bachelor's degree, a minimum of 4+ years of industry experience required)
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimisation,  and analytics
  • Knowledge of experimental design and analysis
  • Experience with exploratory data analysis, statistical analysis, and testing, and model development
  • Ability to use a language like Python or R to work efficiently at scale with large data sets
  • Proficiency in languages and tools like SQL, Python, and Spark

 
Preferred Qualifications

  • 4+ years of industry experience working as a data scientist/Engineer or similar
  • Experience with causal inference techniques to evaluate the causal relationships with variables
  • Experience building machine learning models
Is a Remote Job?
No

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