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发帖数: 342 | 1 Job ID: 875797
Decision Scientist
http://careers.microsoft.com/careers/en/gbl/home.aspx
Decision Scientist
Interested in working on strategic initiatives that allow for creativity and
room for growth? Are you an expert in statistical analysis? Are you a
strong believer in using data to drive the best business decisions? Are you
passionate about your work and believe you can make a difference?
The Risk Analytics team is responsible for evaluating online transactions
for potential fraud. Our job is to provide quantitative assessments of all
customers and identify those individuals who pose the most risk to our
businesses. We are currently looking for a high-caliber individual to join
our team and to help create the most sophisticated analytic solutions aimed
at minimizing risk for the company.
The Decision Scientist would analyze, optimize and implement computational
rules used to monitor and control activity on the Cloud and Enterprise
Division’s (C&E) Commerce Platform (CP). We are looking for a customer-
focused, detail-oriented, results-driven analytic professional with great
communication skills and a strong knowledge of databases and statistical
techniques that ideally has a background in the payments and fraud
prevention space. Because of the number, complexity, and interdependency of
rules, the optimization of rule sets is a non-trivial statistical, machine
learning and text analytics problem that spans numerous databases and data
dimensions.
Responsibilities:
1. Use statistical techniques to design predictive models that detect fraud
and other ecommerce risks. Iteratively test, refine, and improve the
algorithms. In this role, the Decision Scientist will be required to be
expert in building predictive, statistically valid models.
2. Implement and update computational rules to monitor and enforce Risk
policies. Manage the day-to-day aspects of systems (SAS, data sources,
workflow systems, etc.) to ensure that the modeling and production
infrastructure is optimized. In this role, the Decision Scientist will work
closely with developers and other data/systems providers (internal and
external) to enhance systems and trouble-shoot data issues, etc.
3. Improve rule performance by analyzing misclassification cases, hit rates,
and customer feedback. Organize, document and simplify rules. Contributes
to global rule set by building best-practice rules and understanding
international needs and Payment types.
4. Understanding partners’ business processes and recommend data attributes
that can contribute to identifying risk and possible fraud. Collaborates
with relevant team members, Developers and Program Managers to ensure rules
are in alignment with business needs.
5. Assists the Software Development and Program Management teams in testing
and deploying rule set.
Requirements:
1. Master’s degree in Statistics, Operations Research, Machine Learning or
other related fields (Ph.D. preferred) and a minimum of 5-7 years’ related
work experience.
2. 5+ years in database record manipulation (mainly SAS/SQL) and statistical
modeling techniques (regression, CHAID, neural networks, cluster analysis,
etc.).
3. 3+ years’ experience with a statistical programming package such as SAS/
SPSS/R is required.
4. Candidates must be able to pass a background examination.
Preferred Skills:
1. Proven ability with recent, hands-on modeling, optimization, and machine
learning or text classification algorithms.
2. Strong understanding of predictive modeling, data manipulation, and
import/export procedures within above mentioned packages is needed. Creation
and understanding of macros is strongly preferred.
3. Ability to be flexible enough to jump in and act as a team-member, taking
immediate ownership of unanticipated fraud scenarios, and responding to ad
hoc requests requiring database skill to solve. To that end, the candidate
must be comfortable writing SQL queries, stored procedures and/or trigger
jobs.
4. Additionally, the candidate must demonstrate high energy/creativity, a
passion for analyzing highly complex data sets, strong communication and
project management skills, strong debugging skills, an entrepreneurial
spirit, a relentless customer-focus, a practical understanding of
quantitative methods, and superb attention to detail. |
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