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Nitin Nayak, Ph.D. Email & Phone Number

Adjunct Lecturer, Masters in Applied Analytics at Columbia University School of Professional Studies
Location: United States 8 work roles 3 schools
2 work emails found @ibm.com 3 phones found area 914 and 212 LinkedIn matched
✓ Verified Jul 2026 4 data sources Profile completeness 100%

Contact Signals · 2 work emails · 3 phones

Work email n****@ibm.com
Direct phone (914) ***-****
LinkedIn Profile matched
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Role
Adjunct Lecturer, Masters in Applied Analytics
Location
United States
Company size

Who is Nitin Nayak, Ph.D.? Overview

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Nitin Nayak, Ph.D. is listed as Adjunct Lecturer, Masters in Applied Analytics at Columbia University School of Professional Studies, a with 567 employees, based in United States. AeroLeads shows a work email signal at ibm.com, phone signal with area code 914, 212, and a matched LinkedIn profile for Nitin Nayak, Ph.D..

Nitin Nayak, Ph.D. previously worked as Adjunct Lecturer, Masters in Business Analytics at Columbia University School Of Professional Studies and Principal Data Scientist at Ibm. Nitin Nayak, Ph.D. holds Ph.D. (Robotics), Engineering from Penn State University.

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Email format at Columbia University School of Professional Studies

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*@ibm.com
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Profile bio

About Nitin Nayak, Ph.D.

In my current position, I teach graduate students pursuing masters in business analytics offered by the School of Professional Studies at Columbia University. I have past experience in leading teams to innovate, develop, and commercialize high-impact technology solutions for various cross-industry business and consumer problems in retail, electronics, government, and financial services industries. My previous projects have improved life insurance underwriting by removing time-consuming and costly lab testing for majority of insurance applicants using data-driven predictive models. I have helped pricing actuaries to rapidly compute insurance premiums for excess-loss coverage for health insurance clients using Montecarlo simulation to model probability distribution of medical excess-losses. Previously, my Enterprise Risk Mgmt workbench, with integrated statistical risk models and knowledge management models, was well-received by CFOs at Fortune 500s and by officials in US DoD and US Treasury. Known for transferring technical ideas across domains, I am a risk-taker and have learnt much from launching a social-networking startup, myPEPR.com.I am comfortable with several technologies including deep learning, machine learning, text analytics, linear and integer optimization techniques, simulation modeling and analysis (montecarlo, discrete-event), and process modeling. Having worked on several team projects I am equally at ease with both business and technical aspects of a project. My educational background includes MS/Ph.D. in mechanical engineering (robotics) from the The Pennsylvania State University and MBA in marketing and finance from NYU Stern School of Business.Congenial and enthusiastic, I am comfortable working with global teams, communicating with senior business executives and technical audiences, and presenting complex ideas in simple terms.

Listed skills include Machine Learning, Algorithms, Analytics, Java, and 46 others.

Current workplace

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Columbia University School of Professional Studies
Columbia University School Of Professional Studies
Adjunct Lecturer, Masters in Applied Analytics
United States
Employees
567
AeroLeads page
8 roles

Nitin Nayak, Ph.D. work experience

A career timeline built from the work history available for this profile.

Principal Data Scientist

Ibm

Armonk, New York, Ny, Us

Principal Data Scientist for Cognitive Enterprise Services, IBM Finance & Operations

Sep 2019 - May 2023

Senior Analytics Professional

Zurich, Zurich, Ch

Swiss Re's Digital & Smart Analytics group provides innovative, data-driven analytical solutions and services to Swiss Re business units and clients to significantly improve insurance industry processes. My key achievements include• Lab Waiver Triage in Underwriting: Developed mortality risk-neutral machine learning model to identify life insurance applicants for whom costly, time-consuming lab-testing can be waived. Performs at 66% STP rate with 96% precision• Non-smoker Triage in Underwriting: Developed predictive model to identify non-smokers without lab-testing thereby reducing costs and wait time from 4-6 weeks to minutes. Performs at precision (98%) with recall (93%)• Medical Excess Loss Reinsurance: Developed montecarlo simulation solution to quote premium for Swiss Re's excess loss coverage insurance sold to health plans and self-insured businesses.• Electronic Health Records for Underwriting: Leveraged bluebutton library to process CDA-based records for structured data and exploring Amazon Comprehend Medical for physician notes.• Managed a team of data scientists, consultants and software engineers to deploy predictive model as a web service to be integrated within clients' automated life underwriting systems.

Jul 2015 - May 2019

Senior Data Scientist / Senior Manager

Aig

New York, Ny, Us

AIG Science group's mission is to apply data-driven decision making to create significant value in all aspects of insurance. My responsibilities include:• Developed gradient boosted decision tree model using structured and unstructured data to improve subrogation of insurance claims related to auto insurance. This and other models recovered $30+M subrogation amount for AIG from other insurance carriers.• Developing fraud detection model to identify insurance claims with high fraud suspicion level. • Managed a team of 4 PhD/MS level data scientist and engineers to deploy several predictive models into production environment 1 month ahead of schedule.

May 2014 - Jun 2015

Founder & Ceo

Mypepr.Com

myPEPR.com is an event-centric social networking platform targeted at local communities and metro-area residents and integrates local events, shared interests and calendar availability of friends. Responsibilities included:• Conceived and designed myPEPR to promote face-to-face social interaction within local communities based on shared interests and calendar availability of friends for local events.• Secured seed capital and built minimum viable product, comprising social networking platform, activity catalog, event calendar and recommender module, within 6 months with 6 developers. • Deployed myPEPR on Amazon EC2, identified target markets and conducted series of pivots selecting promising ones. Signed-up several local NY communities for pilots.myPEPR platform can also be deployed as a Corporate Innovation platform, Employee Volunteering platform, and other collaborative applications that integrate project catalog, member interests and calendar availability. Contact nnayak@myPEPR.com.

Jan 2013 - Jun 2014

Senior Technical Staff Member

Ibm

Armonk, New York, Ny, Us

Developed and deployed innovative solutions in areas of business analytics, enterprise risk management, enterprise architecture modeling, and SOA-based solutions. Projects included:• Customer Service Analytics to improve effectiveness of IBM call-center operations • Contract Performance Analytics to predict problematic consulting contracts early in their lifecycle. • Product Recommendation Analytics to predict probability of selling software products for client-specific business context. • Enterprise Risk Management Workbench with statistical risk modeling integrated with knowledge-management models for risk modeling, risk analysis, investment prioritization, risk knowledge sharing, and ERM maturity assessment.• Service-oriented Architecture (SOA) architecture to build novel PLM solutions for automotive industry by integrating third party PLM services.

Mar 2002 - Jun 2013

Research Staff Member

Ibm

Armonk, New York, Ny, Us

Developed innovative algorithms and tools for managing supply chain, improving manufacturing operations, and creating business services mashups. Projects included:• Supply Chain Management applications to plan supply volumes for uncertain demand and to collaboratively plan supply across multiple vendors. • Optimization application to significantly improve electronic card assembly process by pick-and-place robots.

Mar 1993 - Mar 2002
3 education records

Nitin Nayak, Ph.D. education

Ph.D. (Robotics), Engineering

Penn State University

Mba, Finance & Marketing

Nyu Stern School Of Business

Bachelor Of Engineering (B.Eng.), Mechanical Engineering

Visvesvaraya National Institute Of Technology
FAQ

Frequently asked questions about Nitin Nayak, Ph.D.

Quick answers generated from the profile data available on this page.

What company does Nitin Nayak, Ph.D. work for?

Nitin Nayak, Ph.D. works for Columbia University School of Professional Studies.

What is Nitin Nayak, Ph.D.'s role at Columbia University School of Professional Studies?

Nitin Nayak, Ph.D. is listed as Adjunct Lecturer, Masters in Applied Analytics at Columbia University School of Professional Studies.

What is Nitin Nayak, Ph.D.'s email address?

AeroLeads has found 2 work email signals at @ibm.com for Nitin Nayak, Ph.D. at Columbia University School of Professional Studies.

What is Nitin Nayak, Ph.D.'s phone number?

AeroLeads has found 3 phone signal(s) with area code 914, 212 for Nitin Nayak, Ph.D. at Columbia University School of Professional Studies.

Where is Nitin Nayak, Ph.D. based?

Nitin Nayak, Ph.D. is based in United States while working with Columbia University School of Professional Studies.

What companies has Nitin Nayak, Ph.D. worked for?

Nitin Nayak, Ph.D. has worked for Columbia University School Of Professional Studies, Ibm, Swiss Re, Aig, and Mypepr.Com.

How can I contact Nitin Nayak, Ph.D.?

You can use AeroLeads to view verified contact signals for Nitin Nayak, Ph.D. at Columbia University School of Professional Studies, including work email, phone, and LinkedIn data when available.

What schools did Nitin Nayak, Ph.D. attend?

Nitin Nayak, Ph.D. holds Ph.D. (Robotics), Engineering from Penn State University.

What skills is Nitin Nayak, Ph.D. known for?

Nitin Nayak, Ph.D. is listed with skills including Machine Learning, Algorithms, Analytics, Java, Software Project Management, Data Analysis, Big Data, and R.

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