BI Quantitative Analyst
Job Summary
Job Description
The Business Intelligence Quantitative Analyst will play a key role in a strategic area, using data to answer complex questions. This role involves cross-functional collaboration to define success metrics, using statistical analysis to understand user behavior and influence product features. Daily responsibilities include in-depth analysis to uncover opportunities, building and maintaining statistical models, collaborating with engineering on data infrastructure, and working with business teams on analysis requirements. The role requires a candidate who is passionate about data and its application.
Must have:
- BS or MS in a quantitative discipline (e.g., Computer Science, Statistics).
- Experience with data wrangling tools like Python, SQL, Hive, R, etc.
- Experience in regression, SVM, boosting, HMM, or clustering techniques.
Good to have:
- Experience working on games.
6 skills required
Job Details
The Business Intelligence Quantitative Analyst plays a key role in one of the most strategic areas of the company. You must be passionate about using data to answer complex questions. You will work cross-functionally to define meaningful success metrics for the company, use statistical analysis and data mining techniques to better understand user behaviors and influence product features.
What you will do everyday:
- Conduct proactive in-depth analysis and modeling to uncover hidden opportunities; communicate insights to product, engineering, and management teams.
- Build and maintain complex statistical models that learn from and scale to millions of users.
- Collaborate with engineering on design and implementation of data infrastructure to support analytics needs.
- Work with business teams on requirements and goals for ad-hoc analysis.
Required Skills
- BS or MS in Computer Science, Statistics, Math, Engineering, or another quantitative discipline; 3+ years of industry experience a plus.
- Proven ability to deal and thrive with multiple imperfect, mixed, varied, and inconsistent data sources; expert knowledge in one or more of the following languages/tools to wrangle and understand data: Python, SQL, Hive, R, Matlab, Spotfire, Tableau.
- Experience in one or more of the following techniques: regression, SVM, boosting/ensemble methods, HMM, graph theories, clustering techniques, etc.
Preference will be given to candidates who have:
- Strong preference will be given to candidates with experience working on games.
Salary Package
We offer highly competitive and lucrative packages that could vary depending on the educational background, work experience, as well as the candidate�s performance in the interview.
Deadline
ASAP!
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