Gagan Jakhu

Associate Consultant

New York City, New York, United States3 yrs 10 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Developed AI systems handling 300K+ transactions daily.
Expert in machine learning and quantitative finance.
Strong foundation in statistics and risk modeling.

Stackforce AI infers this person is a Fintech and SaaS expert with a focus on AI-driven solutions.

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Skills

Core Skills

Quantitative FinanceMachine LearningData ScienceTechnical Support

Other Skills

API IntegrationAlgorithmic TradingCustomer SatisfactionData AnalysisData CleaningData ExtractionDatabase Management System (DBMS)E-commerceEconomicsExploratory Data AnalysisFAISSFinancial EconomicsFinancial MarketsFinancial ModelingLangChain

About

As a Quantitative Finance graduate student at Fordham University’s Gabelli School of Business, I bring a unique blend of AI engineering, machine learning, and data-driven financial insight to solve complex problems at the intersection of finance and technology.I have over 3 years of experience at Sprinklr, where I built and scaled intelligent AI systems using LLMs (OpenAI), LangChain, and Retrieval-Augmented Generation (RAG). My work spanned from building agentic AI workflows to deploying real-time commerce solutions that handle over 300K+ transactions daily across 150+ subsidiaries.I hold a B.Tech degree from NIT Jalandhar and a Postgraduate Diploma in Financial Mathematics, with a strong foundation in Statistics, and risk modeling. My academic research includes developing machine learning-based QSAR models to support drug discovery, showcasing my ability to translate complex data into actionable predictions.Technically, I am proficient in Python, C++, scikit-learn, PyTorch, NumPy, Pandas, and data infrastructure (MongoDB, MySQL). I’m passionate about applying these skills to quantitative finance, algorithmic trading, and fintech innovation.📩 Let’s connect if you're working in AI for finance, Data Science, Machine Learning, or systematic investing.

Experience

Fordham university

Graduate Research Assistant

Aug 2025 – Present · 7 mos · New York, United States · Hybrid

Developed a neural network, based model to predict options prices and benchmarked its performance against the Black–Scholes model, implemented the full pipeline in Python.
Designed and automated a Python workflow to convert cross-sectional datasets into panel dataset for OLS regression analysis, improving efficiency and reproducibility for research project.

PythonNeural NetworksOLS RegressionQuantitative FinanceMachine Learning

Sprinklr

2 roles

Data Scientist

Promoted

Oct 2023 – Jul 2025 · 1 yr 9 mos · On-site

Spearheaded the development of an agentic AI platform at Sprinklr, leveraging LangChain and OpenAI LLMs to orchestrate autonomous agents that dynamically interpret user intents and execute multi-step workflows.
Engineered a Retrieval-Augmented Generation (RAG) system by integrating FAISS-based semantic search with LangChain pipelines, enabling high-precision, context-aware responses from unstructured data sources.
Built NLP-based classification models using transformer architectures (BERT, GPT-based embeddings)
to automatically analyze and categorize customer feedback and survey data across Sprinklr’s client ecosystem,
reducing manual triage workload by 60% and enabling faster, data-driven insight generation.
Designed and implemented a scalable chat commerce platform with real-time cart sync and automated product catalog management, including “Add to Cart” functionality for key clients, enabling 300K+ daily transactions across 150+ subsidiaries and enhancing agent-assisted shopping experiences.

LangChainOpenAI LLMsNLPPythonMachine LearningData Science

Technical Consultant

Jul 2022 – Sep 2023 · 1 yr 2 mos · On-site

Engineered automated data extraction scripts in Python to retrieve client-level identifiers from noisy sources, streamlining preprocessing for downstream statistical analysis.
Led Cross-Team Collaboration and Authored debugging guides, trained teams on product usage and ticket resolution, and spearheaded implementation projects, improving operational efficiency and client success.
Built robust connectors for integrating third-party APIs with internal services, streamlining data flow, and reducing onboarding time by 30% by developing reusable integration modules in Python.

PythonData ExtractionAPI IntegrationTechnical SupportData Science

Dr b r ambedkar national institute of technology, jalandhar

Research Assistant

Aug 2021 – Apr 2022 · 8 mos · On-site

Centre of training & placement,nit jalandhar

2 roles

Placement Coordinator

Jul 2021 – Jun 2022 · 11 mos

Fostered strong relationships with over 30+ corporate partners to expand placement opportunities and increase campus hiring engagement.
Coordinated end-to-end placement activities including pre-placement talks, interview scheduling, and student-recruiter interactions.
Led resume-building workshops and mock interviews, improving student placement readiness and professionalism.
Acted as a key communication bridge between the Placement Cell, students, and recruiters, ensuring seamless execution of all drives.

Internship Coordinator

Aug 2020 – Jul 2021 · 11 mos

Facilitated internship opportunities by identifying potential recruiters, initiating outreach, and circulating verified openings to students.
Conducted surveys and polls to align internship offerings with student interests and career goals.
Guided peers on professionalism, communication, and workplace etiquette through regular mentoring and sessions.
Built early connections with industry professionals via LinkedIn and web research to strengthen the internship pipeline.

Direction educare

Data Science Intern

Jun 2021 – Aug 2021 · 2 mos · Jalandhar, Punjab, India · Hybrid

Cleaned and preprocessed structured and unstructured datasets using Pandas and NumPy, improving data quality and enhancing the accuracy and usability of downstream analytics and modeling workflows.
Collaborated in version-controlled workflows using Git and Jupyter Notebooks, contributing to Python-based exploratory data analysis pipelines and early-stage model development and validation.
Participated in Agile and Scrum sprints using tools like Slack and Jira, gaining practical experience in iterative development cycles and full SDLC within a data science project environment.

Data CleaningExploratory Data AnalysisData Science