Nitish Mallick

As a Founding AI Engineer with 11 years of experience, I thrive on tackling complex challenges with a logical and pragmatic approach. My ambition drives me to take full accountability for innovative solutions, valuing the autonomy and independence required to deliver impactful results.

Experience

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Founding AI Engineer

GalaxiQ · Nov 2025 – Present

Not yet confirmed

• Brand Intelligence Platform: Built a website intelligence engine that continuously crawls client websites to extract and analyze brand identity attributes including brand colors, tone, keywords, logos, positioning signals, and actionable optimization recommendations.
• Deployable Al Customer Support Platform: Developed a production-ready Al chatbot platform deployable on client websites with support for dynamic knowledge base ingestion (PDFs, websites, documents), contextual customer support, ticket creation/tracking, and live admin takeover functionality.
• Al Campaign Generation System: Built a campaign generation platform capable of creating social-media-ready marketing assets including Al-generated images, captions, editable creatives, regeneration workflows, and scheduled publishing capabilities.
• Unified Al Insights Platform: Developed an Al insights assistant that provides conversational analytics across multiple business systems including social media performance, ticketing systems, brand monitoring, and operational product intelligence with continuously updating contextual memory.
• End-to-End Product Architecture Ownership: Architected and implemented the complete backend, Al infrastructure, retrieval systems, orchestration layers, and deployment workflows from scratch across all products, ensuring scalability and production reliability.

Founding AI Engineer

GalaxiQ AI · Nov 2025 – May 2026

Not yet confirmed

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AI Engineer

HUB · Apr 2025 – Oct 2025

Not yet confirmed

• Fabric Pipline Generator: Designed and implemented an automated system to generate and execute Microsoft Fabric pipelines based on user inputs and uploaded datasets, streamlining data processing workflows.
• YAML Writer (RAG-based): Built a Retrieval-Augmented Generation_(RAG) system that dynamically generates YAML configuration files from user-uploaded data, reducing manual configuration effort.
• Table Model Mapping (Al-driven): Developed an Al-powered column-matching engine that maps table headers between multiple datasets using financial domain knowledge and historical matching records, improving data integration accuracy.
• Codebase RAG (Frontend Component Extraction): Created a codebase-aware RAG system that retrieves and assembles relevant frontend components to automatically generate Ul sections based on user requirements, similar to submodules of Bolt.diy.
• Content Generation Engine: Built an application which will generate marketing images and videos using hugging face open source models.
• Also it will support chat feature where user can keep improving the generated image.

Data Scientist

Newgen Software · Aug 2023 – Mar 2025

Not yet confirmed

• Banking/Financial
• Designed and Implemented Synthetic Data Generation System: Developed a sophisticated system to create real-world-like synthetic data for banking models for Bank 360 Database Development, e.g. generating savings, credit card, mutual fund transactions, etc.
• Model Development: Lead the creation of high-impact models for major banking clients which includes:
• Cross-Sell for Credit Cards
• Loan Collections (PnB Bank)
• Risk Assessment and Pre-Approval (IndusInd Bank)
• Churn Prediction
• Insurance Claim Prediction (State Bank of India)
• Retail/E-commerce
• Personalized Recommendation Engine: Developed advanced machine learning models using NLP techniques to power hyper-personalized product recommendations, including similar and complementary item suggestions, as well as user-item affinity scoring, etc.
• Hyper-Personalized Analytics: Engineered analytics to generate deep insights like customer lifetime value, behavioral segments, etc.
• This insight enabled data-driven marketing strategies and personalized customer experiences, contributing to enhanced customer loyalty and revenue growth.
• Chat With Data System Development: Created an interactive "Chat with Data" system utilizing LangChain and SQL Agent to establish a seamless LLM (Large Language Models) chain.
• This system enables users to conduct intuitive, natural language conversations directly with data stored in SQL databases.

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Data Scientist

Newgen Softwares · Aug 2023 – Mar 2025

Not yet confirmed

• RAG System on Call Transcripts (includes text and tabular data): Used Postgres PGVector to build the vectordb.
• Built the entire brain where it will take user question and retrieve relevant info from DB and then generate diff type of answer based on the question and also return the sources from which it answered.
• LLM Evaluation System(No GroundTruth): Built an evaluation system for LLM where I used the concept LLM as a judge where it will take user question and final answer to give numbers against some defined metrics.
• The metrics calculation methodology has been prompted and fintuned for each LLM evaluation agent.
• Designed and Implemented Synthetic Data Generation System: Developed a sophisticated system to create real-world-like synthetic data for banking models for Bank 360 Database Development, e.g. generating savings, credit card, mutual fund transactions, etc.
• Model Development(Classical): Built classical ML models for banking clients which includes models like Cross-Sell for Credit Cards, Risk Assessment and Pre-Approval, Insurance Claim Prediction, etc.
• Google Cloud end to end system : Developed and Deployed on GCP where the data will be automatically pushed from users database daily and then the python scripts will run on VM instance as scheduled and then results will be pushed to dasboard.
• Personalized Recommendation Engine and KPI's: Built hyper-personalized product recommendations, including similar and complementary item suggestions, etc.
• Also, Engineered analytic KPIs to generate deep insights like customer lifetime value, behavioral segments, etc
• Researched Responsible AI (RAI) Frameworks: Researched to design an abstract framework for Al and Gen-Al systems where it needs to ensure certain pillars to build users trust and overall reliability.

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Data Science Intern

Minfy · Apr 2023 – May 2023

Not yet confirmed

• Simulated model drift scenario using a single dataset

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Data Analyst

DP World · Oct 2021 – Jun 2022

Not yet confirmed

• Designed a MIS (Management Information System) on Excel with required KPIs which saved around Rs.70 lacs on MoM basis.

Research Intern

Praja Foundation · Sep 2020 – Nov 2020

Not yet confirmed

• Working on the policy design regarding the allocation of the Housing sector and how empty houses can be used for renting and other uses.

Summer Intern

DFCCIL · Jul 2020 – Aug 2020

Not yet confirmed

• Learned about what State of the art technology is used in DFCCIL.
• Worked on Technological Comparison of conventional and upgraded DFC's

Summer Intern

Indian Railways · Jun 2019 – Jul 2019

Not yet confirmed

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Streets for All

United States-India Educational Foundation (USIEF), New Delhi · Dec 2018 – Dec 2018

Not yet confirmed

• Workshop on redesigning streets.