Data Science/Quant Research Analyst

Company Name:
Open Systems Technologies

Job Description:
As part of the data, quantitative and technology teams, you work along-side with seasoned media and quantitative trading veterans on the development of cutting edge algorithmic media trading and optimization strategies.
Major Quantitative Initiatives:
Build digital media trading data platform connecting exchanges, ?big-data?-management platforms and third party data sources.
Monitor and analyze real time and historical trading activity.
Analyze, develop and evaluate performance of custom data segments
Predict advertisement efficiency based on factors (e.g. user segment and displayed creative).
Develop programmatic media buying strategies that optimize acquisition rates and spending budgets.
Develop bidding algorithms in a real-time second price auction framework.
Develop selling-side strategies that optimize inventory liquidation and monetization.
Develop profitable trading strategies.
Building audience and look-a-like models for client and inventory targeting
Provide ad-hoc quantitative analysis aiding the trading desk with tactical insights on sell-side optimization and campaign delivery.
Research Topics:
Factor regression and estimation, clustering, statistical modeling
Second price auction, game theory, bidding-strategy
Time-series modeling, adaptive learning, explore-exploit schemes
At least 2-4 years of experience in a quantitative data driven field
A passion for both digital marketing and data analytics
Independent thinker with strong ability to prioritize tasks within teams
Ability to clearly explain complex technical ideas to multiple audiences both verbally and in writing
Ability to work well with others and work in cross functional teams
Comprehensive knowledge of ad technologies, how they work, and how to troubleshoot
Desired Skills:
Advanced degree is preferred. Bachelor?s degree in statistics, mathematics, economics, engineering fields required.
Strong background and research interest in applied mathematics, statistical modeling, algorithms, data-mining and machine learning techniques
Able to code in R, Python, Scala and other languages as necessary. Experience with SAS, SPSS, R or other advanced analytics software packages
Experience with ad-serving tools and trading platforms (e.g. Google DFA, Atlas, AppNexus)
Familiarity with big-data, low latency and web-technology (e.g. Hadoop / MapReduce, Hive, Cassandra, Storm, Scala, Spark, JSON)
Experience / familiarity with concepts of data architecture and SQL
Expert in Microsoft Excel

Don't Be Fooled

The fraudster will send a check to the victim who has accepted a job. The check can be for multiple reasons such as signing bonus, supplies, etc. The victim will be instructed to deposit the check and use the money for any of these reasons and then instructed to send the remaining funds to the fraudster. The check will bounce and the victim is left responsible.