Job Description :
Data Scientist
Chicago, IL
1 year
Domain Experience:
3+ years-experience in machine learning and predictive analytics
Strong knowledge of statistics and predictive methods such as SEM, multiple and logistic regression, Bayesian modeling, support vector machines, neural net training, tree induction techniques like CHAID, CART, random forest, random tree, etc.
Able to translate complex data into actionable insights and recommendations.
Strong understanding of the Financial Services is required.
Experience with financial models, risk models, marketing cross-sell, up-sell, retention, and customer lifetime value models preferred.
15 years plus Real world experience in monetizing models and making money (Retail or Distribution industry)
Expert in R, Vanatge etc (Sri you know our environment, some one who can coach our team)
Soft Skills:
Multi-tasking and priority setting – ability to effectively manage multiple projects of varying complexity.
Ability to work independently and as part of a team.
Excellent communication skills, both written and verbal.
Technical Skills/Experience:
Experience with statistical modeling
Practical experience in preparing data for machine learning
Practical experience in using and designing regression, SVM, clustering, and other classification models.
Nice to have experience in optimization
Nice to have experience in Spark, Tensorflow, parallel computation
Experience with large data stores, both SQL and noSQL (e.g. Hadoop)
Python, R, Matlab
Node.js, Scala for services, Postgres for the database
Kubernetes, for deployment and Devops
AWS for infrastructure, leveraging EC2, S3, SWF, CloudFront, Route53, and much more
Proven capabilities in presenting technical findings to non-technical audiences