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Data Science Analyst Pyspark and AB Testing

AT Infosys
Infosys

Data Science Analyst Pyspark and AB Testing

Austin, TX

In the role of Senior Lead Analyst - Data Science you will be responsible for solving business problem for our Retail/CPG clients through data driven insights. Your role will combine a judicious and tactful blend of Hi-Tech domain, Analytical experience, Client interfacing skills, and solution design and business acumen so your insights not only enlighten the clients but also pave the way for launching deeper into future analysis. You will advise clients and internal teams through short burst high-impact engagements on identifying business problem, solving business problem through suitable approaches and techniques pertaining to learning and technology. You will effectively communicate data-derived insights to non-technical audiences appropriately and mentor junior or aspiring consultant/data scientists. You will play a key role in building components of a framework or product while addressing practical business problems. You will be part of a learning culture, where teamwork and collaboration are encouraged, excellence is rewarded, and diversity is respected and valued.

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Required Qualifications:
  • Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
  • All applicants authorized to work in the United States are encouraged to apply.
  • Candidate must live within commuting distance of Cupertino, CA or Austin, TX, or be willing to relocate. Travel within the US may be required.
  • At least 4 years of experience in Information Technology
  • At least 4 years applied experience in exploratory data analysis, devising, deploying and servicing statistical models
  • Strong hands-on experience with data mining and data visualization
  • Strong proficiency and hands on experience in A/B Testing
  • Strong proficiency and hands on experience in SQL for developing data pipelines
  • At least 4 hands on experience using Python, Advanced SQL and PySpark
  • At least 3 years using Tableau for data visualization
  • Able to create Data pipeline to source and transform Data
  • Very strong communication skills (Written & Verbal)
Preferred Qualifications:
  • MBA or MS from prestigious University in area of quantitative discipline such as Statistics, Applied Math, Operations Research, Computer Science, Engineering or Physics
  • Marketing domain background (Web analytics, click stream data analysis, and other KPI's on marketing campaigns)
  • Knowledge of Machine Learning techniques
Estimated annual compensation range for candidate based in the below locations will be
  • Cupertino,CA: $73,000 to $162,010
Along with competitive pay, as a full-time Infosys employee you are also eligible for the following benefits :-
  • Medical/Dental/Vision/Life Insurance
  • Long-term/Short-term Disability
  • Health and Dependent Care Reimbursement Accounts
  • Insurance (Accident, Critical Illness , Hospital Indemnity, Legal)
  • 401(k) plan and contributions dependent on salary level
  • Paid holidays plus Paid Time Off
The job may entail extensive travel. The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face.

Client-provided location(s): Austin, TX, USA
Job ID: Infosys-132228BR
Employment Type: Other

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Life Insurance
    • HSA
    • Short-Term Disability
  • Parental Benefits

    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • On-site/Nearby Childcare
  • Office Life and Perks

    • Commuter Benefits Program
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
    • Sabbatical
  • Financial and Retirement

    • 401(K)
    • Relocation Assistance
  • Professional Development

    • Learning and Development Stipend
  • Diversity and Inclusion

    • Employee Resource Groups (ERG)