Avishek Nag — Co-Founder

An accomplished Machine Learning specialist with several years of deep experience in design/development of complete ML systems that includes parametric and non-parametric Machine learning models such as , 1) Traditional ML models 2) Statistical Reinforcement Learning 3) Probabilistic Graphical Model, Random Graphs 4) Survival Analysis 5) Stochastic Finance, stochastic modelling, Monte Carlo Methods 6) NLP Have sound knowledge & work experience in Survival Analysis (Weibull Model, Cox-PH model, Accelerated Failure Time model), Stochastic Computational Finance (Jump models, Black-Scholes Model), Nonparametric Statistical methods etc. I am also the author of the following books a) Survival Analysis with Python (CRC Press) b) Pragmatic Machine Learning with Python Trusted leader and change agent with a superior track record of motivating people right from the grass-root level and taking subordinates into confidence for implementing new and innovative ideas.

Stackforce AI infers this person is a Fintech and Machine Learning specialist with extensive experience in developing complex algorithms.

Location: Bengaluru, Karnataka, India

Experience: 19 yrs 4 mos

Skills

Machine Learning
Survival Analysis
Stochastic Finance
Probabilistic Graphical Model
Cloud Development

Career Highlights

Expert in designing complete ML systems.
Authored multiple books on Machine Learning and Finance.
Proven track record in motivating teams and driving innovation.

Work Experience

Apress

Author of "Stochastic Finance with Python" (1 yr 3 mos)

Self-employed

Independent Researcher (3 yrs 6 mos)

CRC Press

Book Author (Survival Analysis with Python) (7 mos)

Confidential

Principal Engineer - Machine Learning (2 yrs 3 mos)

upGrad

Upgrad Xpert - Machine Learning (3 mos)

BPB

Book Author (Pragmatic Machine Learning) (5 mos)

Medium; Towards AI; Towards Data science; The Startup;

Blogger - AI/Machine Learning (7 yrs 2 mos)

Cisco

Machine Learning Specialist (2 yrs 2 mos)

Eka Software Solutions

Lead Engineer (1 yr 4 mos)

VeraHQ

Principal Software Engineer (8 mos)

MobileIron

Senior Software Engineer (6 mos)

VMware

Senior Applications Developer (1 yr 11 mos)

Xebia

Senior Consultant (1 yr)

Computer Sciences Corporation

Lead Consultant - Application Development (1 yr 5 mos)

Tech Mahindra

Senior Technical Associate (5 mos)

Connectiva Systems

MTS II (1 yr 11 mos)

Cognizant Technology Solutions

Programmer Analyst (2 yrs 4 mos)

Education

Master of Technology (MTech) at Birla Institute of Technology and Science, Pilani

B.Tech at West Bengal University of Technology, Kolkata

Avishek Nag

Co-Founder

Bengaluru, Karnataka, India19 yrs 4 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in designing complete ML systems.
Authored multiple books on Machine Learning and Finance.
Proven track record in motivating teams and driving innovation.

Stackforce AI infers this person is a Fintech and Machine Learning specialist with extensive experience in developing complex algorithms.

Contact

Skills

Core Skills

Machine LearningSurvival AnalysisStochastic FinanceProbabilistic Graphical ModelCloud Development

Other Skills

Mathematical optimizationComputational FinanceComputational GeologyStatistical AnalysisPython framework designPythonStochastic CalculusStochastic Computational FinanceBlack-ScholesStochastic Differential EquationsProbabilityMachine Learning algorithmsXAIRandom GraphStatistical Graph estimation

About

Experience

19 yrs 4 mos

Total Experience

1 yr 7 mos

Average Tenure

3 yrs 6 mos

Current Experience

Apress

Author of "Stochastic Finance with Python"

Sep 2023 – Dec 2024 · 1 yr 3 mos · Bangalore Urban, Karnataka, India · Remote

Authored "Stochastic Finance with Python"
From back cover -
"Journey through the world of stochastic finance from learning theory, underlying models, and derivations of financial models (stocks, options, portfolios) to the almost production-ready Python components under cover of stochastic finance. This book will show you the techniques to estimate potential financial outcomes using stochastic processes implemented with Python.
The book starts by reviewing financial concepts, such as analyzing different asset types like stocks, options, and portfolios. It then delves into the crux of stochastic finance, providing a glimpse into the probabilistic nature of financial markets. You’ll look closely at probability theory, random variables, Monte Carlo simulation, and stochastic processes to cover the prerequisites from the applied perspective. Then explore random walks and Brownian motion, essential in understanding financial market dynamics. You’ll get a glimpse of two vital modelling tools used throughout the book - stochastic calculus and stochastic differential equations (SDE).
Advanced topics like modeling jump processes and estimating their parameters by Fourier-transform-based density recovery methods can be intriguing to those interested in full-numerical solutions of probability models. Moving forward, the book covers options, including the famous Black-Scholes model, dissecting it from both risk-neutral probability and PDE perspectives. A chapter at the end also covers the discovery of portfolio theory, beginning with mean-variance analysis and advancing to portfolio simulation and the efficient frontier.
"
Link:
https://link.springer.com/book/10.1007/979-8-8688-1052-7

PythonStochastic FinanceStochastic CalculusStochastic Computational FinanceBlack-ScholesStochastic Differential Equations+2

Self-employed

Independent Researcher

Nov 2022 – Present · 3 yrs 6 mos

Self funded research on discrete topics - Mathematical optimization, Survival Analysis, Computational Finance, Computational Geology, Chaotic Dynamical System, Statistical Analysis.
Designing a Python framework for stochastic finance

Mathematical optimizationSurvival AnalysisComputational FinanceComputational GeologyStatistical AnalysisPython framework design+1

Crc press

Book Author (Survival Analysis with Python)

May 2021 – Dec 2021 · 7 mos

Released on 17th December, 2021
https://www.routledge.com/Survival-Analysis-with-Python/Nag/p/book/9781032148267

Survival AnalysisPythonStatistical Analysis

Confidential

Principal Engineer - Machine Learning

Aug 2020 – Nov 2022 · 2 yrs 3 mos · Bangalore Urban, Karnataka, India

Designing Machine Learning algorithms for System/Network topology stack discovery.
Designing XAI (Explainable AI) based algorithms to identify processes responsible for any framework
Working on Probabilistic Graphical Model to decode different flows of third-party black-box web applications. Proposed solution uses Random Graph & Statistical Graph estimation methods to construct a graphical model of flows

Machine Learning algorithmsXAIProbabilistic Graphical ModelRandom GraphStatistical Graph estimationMachine Learning

Upgrad

Upgrad Xpert - Machine Learning

Jan 2020 – Apr 2020 · 3 mos · Bengaluru, Karnataka

Creating ML content for upGrad for its "Advanced Certification in Machine Learning and Cloud" course

Bpb

Book Author (Pragmatic Machine Learning)

Nov 2019 – Apr 2020 · 5 mos · Bangalore

"Pragmatic Machine Learning"

Medium; towards ai; towards data science; the startup;

Blogger - AI/Machine Learning

Mar 2019 – Present · 7 yrs 2 mos

https://medium.com/@avisheknag17

Cisco

Machine Learning Specialist

May 2018 – Jul 2020 · 2 yrs 2 mos · Bengaluru Area, India

Designed end to end solution of a system working as Machine Learning as Service (MLaaS). This system is responsible for generating automated recommendations for bug insights of network devices & softwares. It helps to improve the bug scrubbing process of network devices & softwares.
Designed several Machine Learning models that give predictions for different insights. Primarily used NLP, Standard classification techniques. Most of the classifications are multi-lable in nature thus making the system complex.
Designed a framework which can deploy Machine Learning models in a platform-independent lightweight format (PMML) and give predictions from there. It also has an in-built model repository for storing life-cycle states of a model. Predictions are exposed as API to the external system. This deployment system can work as a light-weight alternative to AWS Sagemaker.
Used scikit-learn, scikit-multilearn, gensim and big data technologies like PySpark, Apache Kafka

Machine Learning as ServiceAutomated recommendationsNLPPMMLAPI developmentMachine Learning

Eka software solutions

Lead Engineer

Jun 2016 – Oct 2017 · 1 yr 4 mos · Bengaluru Area, India

Designed a OAuth based security layer for Commodity Analytics Cloud product. It has multitenant cloud authentication connector framework.
Currently working on Spark, MongoDB, Machine learning algorithms (Linear Regression, Clustering) to find out insights from the commodity trading data. Have designed a Spark based machine learning workflow framework. Framework is based on Spark-ML, Spark-SQL
Did analysis on policy breach value recommendations using R. Developed models for skew ness correction of the data
Technologies Used : Apache Spark, MongoDB, Spring Batch, R

Verahq

Principal Software Engineer

Sep 2015 – May 2016 · 8 mos · Bengaluru Area, India

Working with Java, Elastic Search based Analytics, Machine Learning algorithms.
1) design & develop statistical anomaly detection (used B.P. Welford's variance calculation algorithm of streaming data for real time analytics) and alert generation system based on access request of documents
2) implement a machine learning/clustering algorithm (K means clustering) for identifying regions/clusters among access locations of documents

OAuthMachine Learning algorithmsSparkMongoDBRMachine Learning

Mobileiron

Senior Software Engineer

Feb 2015 – Aug 2015 · 6 mos · Bengaluru Area, India

My competency had been in designing and developing Spring Social based SDK for Azure Cloud API as there was no Java SDK for it and Spring Social also does not support it currently like other Cloud APIs (i.e., Facebook, Twitter)

JavaElastic SearchStatistical anomaly detectionClustering algorithmsMachine Learning

Vmware

Senior Applications Developer

Apr 2013 – Mar 2015 · 1 yr 11 mos · Bengaluru Area, India

Over here, I worked as an Architect to design the entire framework of a tool vSAF which has service monitoring & notification capabilities. Not only this, I had established virtual infrastructure for the product using vCloud API (Which included creation of vApp from vApp templates to deploy the vSAF product).

JavaAzure Cloud APICloud Development

Xebia

Senior Consultant

Mar 2012 – Mar 2013 · 1 yr · Gurgaon, India

Computer sciences corporation

Lead Consultant - Application Development

Sep 2010 – Feb 2012 · 1 yr 5 mos · Noida Area, India

Involved in design & development of a product which should work as a messaging platform for Healthcare sectors where different parties are involved in exchanging information through web services. To achieve this, developed a complete registry/repository by implementing ebXML messaging/registry specification published by OASIS.
(Ref:
http://www.ebxml.org/,
https://www.oasis-open.org/committees/tc_home.php?wg_abbrev=regrep). These specifications are open source and its implementation has to be provided by the corresponding product vendor (like we did). The implementation was customized a little bit keeping in mind the requirement of Healthcare sector and also this is IHE-XDS compliant.