Data Scientist

Fraud or Risk modeling, Machine Learning, SKLearn or other ML libraries, Business Intelligence (Tableau, SQL), Python
Full Time
Depends On Experience
Work from home not available Travel not required

Job Description

Position Title: Data Scientist

Location: Menlo Park, CA

Duration: Fulltime


The Role.

As Sr. Data Analyst, you'll provide deeper analysis and valuable insights to unlock opportunities and drive informed business decisions. Evolve the data platform with user-friendly tools, solutions and dashboards so that relevant information can be efficiently gathered and easily interpreted by business teams.


Required Candidate Skills and Experience.

  • BS or MS in Engineering, Math, Statistics, Analytics, or Finance

  • 5+ years of experience working in a fast paced environment as a Sr. Data Analyst or Data Scientist.

  • 2+ Years specializing in Fraud or Risk modeling

  • Machine Learning - working with ML frameworks such as SKLearn or other ML libraries

  • Excellent quantitative skills and a deep understanding of statistical methods, and an ability to inspire confidence in data-driven decision making

  • Experience working with Data Warehouse (how we organize data), Business Intelligence Solutions (Tableau etc., Databases (SQL), Postgres etc.), Programming (Python, XML, JavaScript, or ETL frameworks) Experience with running A/B tests and familiar with Experimentation platforms

  • Proficient with Google Analytics, Hotjar and similar Web Analytics products

  • Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc.)

  • Understanding of eCommerce and Retail will be a big plus

  • Exhibit general curiosity to go deeper to understand business problems and surface interesting facts.

Thanks & Regards,

Zafar Parkar | Xoriant Corporation

W: 408-743-4434

1248, Reamwood Ave, Sunnyvale, CA 94089

Feel free to email me at zafar.parkar(at)

Posted By

Zafar Parkar

1248 Reamwood Ave Sunnyvale, CA, 94089

Dice Id : xorca001
Position Id : DA1004
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