Role Summary / Purpose
Highly motivated self-driven Engineer in statistics / predictive modeling / data quality to lead and guide multi-disciplinary project teams addressing key challenges for different businesses. Creation of intellectual property will be a key expectation in this role.
As a senior data scientist in the Modeling and Optimization, you will create and guide programs to invent and deliver predictive modeling and decision technologies for diverse businesses such as Finance, Aviation, Transportation, Oil and Gas and Healthcare.
You will lead and drive programs in areas such as statistical algorithms for processing massive time series data, statistical risk modeling and development of novel algorithms for detecting and correcting anomalies in complex data. Typical applications include developing novel algorithms for early warning systems, building models for medical prognostics and systems for anomaly detection / correction in monitoring and diagnostics data. You will be working with some of the sharpest business minds across the globe on some of the most challenging business problems
Qualifications / Requirements
We are looking for accomplished Fresh Graduates / colleagues with 1-2 years of experience, track record of project management, and demonstrated ability to invent new approaches and/or apply recent methodological advances in data science to solve applied problems. Candidates should hold an MTech or MS in Industrial Engineering, Mathematics, Computer Engineering, Computer Sciences, Statistics with an excellent academic record and practical experience with recent advances in mathematical & computational sciences and statistical modeling.
The candidate should have a demonstrated strong foundation in probability, statistical theory with a deep understanding of statistical estimation, hypothesis testing, linear and logistic regression. A solid grounding in applied statistics including expertise in at least one of the following is a must: Reliability models, Bayesian modeling, statistical classification, cluster analysis, time series analysis, forecasting and multivariate statistics. Possessing strong Implementation and Programming Skills in one or more of Java, Python, SAS, R, Python, Matlab is a must.
Prior experience working with very large datasets using Big Data tools and platforms (Hadoop, PIG / HIVE / Mahout) is highly desirable. Proven ability to lead complex projects with multi-disciplinary teams and ability to work with global businesses to create new programs is a must. Expertise in modelling the behavior of a complex real time dynamic system.
PhD in Industrial Engineering, computer science, Comp Engg, Statistics, Mathematics, Statistics or related field
Strong interpersonal skills
Excellent written and verbal communication skills
Experience working with Financial engineering data – aviation, healthcare, transportation, energy, oil & gas, etc
Send in your resume: email@example.com