Role: Sr. Data Scientist
Duration: Full Time / Permanent
Location: Memphis, TN

Overall Responsibilities:

1. Senior data scientist.
2. Research various analytical approaches.
3. Recommend and develop mathematical algorithms for related business problems.
4. Communicate and direct development teams on implementation of statistical models.
5. Interface with Business users and gather feedback on delivered analytical data.
6. Deploy solutions on to big data platforms.

Functional Responsibilities:

1. Work on one of following initiatives within Predictive Client Analytics group: RFM recommendations, CCAR and other projects TBD.
2. Validation of analytical approaches produced by vendor and 3rd party consulting teams.
3. Developing data validation methods.

Required Skills:

Technical / Analytical Skills:

1. Excellent understanding and experience with application of machine learning concepts and techniques (linear/logistic regression, clustering, classification, PCA, Naive Bayes, association rules, Collaborative Filtering, recommendation techniques etc.).
2. Experience with regression techniques for modeling the relationship between an output variable and several input variables.
3. Experience with Big Data technologies.
4. Experience with visualization tools like Tableau.
5. Experience creating interface specification documents, attribute mapping documents, functional specifications.
6. Experience with web scraping.
7. Experience with Text Matching applications.

Nice to have:

1. Understanding of regulatory guidelines (CCAR, Basel) around Model Risk Management.
2. Working knowledge of various Fixed Income and Equities products, for example Derivatives, FX and Cash Equities.

Essential Skills:

1. Strong verbal and written communication skills.
2. Strong research skills.
3. Python, R, SQL, Hive, Spark.
4. Statistical analysis: To understand and work around possible limitations in models.
5. Being able to develop hypothesis and test the Hypothesis with careful experiments.
6. Research and implement data mining machine learning algorithms in supervised and unsupervised learning areas.
7. Should have experience with time series modeling.
8. Should have experience with optimization approaches.
9. Familiarity with the Big Data Ecosystem tools: Hadoop, Hive, Impala, Mahout, Spark (Spark SQL, MLLib), Hbase and be comfortable with the using the tools.
10. Strong experience in data manipulation using SQL on Hive/Impala or other Databases.
11. Experience in developing and deploying model with Mahout, Spark MLLib is preferable.
12. Must be proficient in programming either R/Python/Scala.
13. Should have experience in Financial services industry - Capital market would be preferable.
14. Should have exposure to Data Visualization tools: Tableau (Preferable)/Qlikview/Excel.

Additional Information

All your information will be kept confidential according to EEO guidelines.