VP - Data Science/Machine Learning - Startup - IIT/BITS/NIT/ISI

Our client is a fast growing technology company based in India with operations globally working in the financial technology industry. They have raised upwards of 100M USD in venture capital (with the last round, early this year). They are looking for a suitable candidate to head their data science division. This person will report to the CTO and work closely with the R&D and technology teams.

Primary Responsibilities :

- Lead, Recruit and Mentor a team of data science professionals

- Provide data/report support for complex data mining projects.

- Generate and execute required analytical programming with minimal supervision.

- Manage data audit steps to ensure data quality.

- Leverage R, Matlab, SPSS, Python, SQL & Excel to dig into data to extract meaning from information.

- Produce appropriate and effective project deliverables including: sample diagnostics, customer profiles, complex queries, data mining, model algorithms, gains charts, modelscore distributions, etc., with some supervision and zero defect.

- Demonstrate a strong understanding of project scope, data extraction methodology, design of dependent and profile variables, logic and design of data cleaning, exploratory data analysis and statistical methods.

- Produce timely and error-free deliverables in an efficient manner, managing multiple tasks and varying project scopes.

General Qualifications :

- BE/MTech in EEE/CS/Statistics/Applied Math/Physics

- IIT/BITS/NIT/Tier 1 US universities/ISI preferred

- PhD in CS/EEE/Statistics/Applied Math/Physics is a big plus

- Should have worked in cross functional teams before

At least 5+ year experience in following work areas:

- Predictive Modeling & Data Mining

- Machine Learning

- Statistical Model Development

- Analytics

Related Knowledge Base:

- Ability to show value of analytics within business processes

- Strong R, Matlab, Python (NumPy, SciPy) or SPSS skills

- Regression (Linear, Logistic, Multinomial), Survival Modeling, Segmentation and Clustering, Decision Tree Analysis

- Machine Learning Algorithm, e.g. SVM, Neural Networks, HMM, Bayesian Belief Networks.

- Mathematical programming and optimization

- Ability to interpret analytical results

- Strong verbal and writing skills

- Big Data and High Performance Computing would be a plus