Aneesha Manke

Data Scientist

Mumbai, Maharashtra, India2 yrs 8 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in building impactful AI solutions.
Proven track record in financial modeling.
Hands-on experience with MLOps and Generative AI.

Stackforce AI infers this person is a Fintech-focused Data Scientist with expertise in AI and machine learning solutions.

Contact

Skills

Core Skills

Machine LearningArtificial Intelligence (ai)Large Language Models (llm)

Other Skills

Python (Programming Language)CommunicationARIMALSTMXGBoostAPI DevelopmentDeep LearningLangChainFAISSGPT-based modelsAnomaly DetectionChatbot DevelopmentLoRAQLoRATeamwork

About

I specialize in building practical, impactful AI solutions and managing the entire lifecycle of a machine learning project from the initial idea to a fully deployed, production-ready system. At Arya.ai, I've applied this skill set to create robust predictive models for financial applications like cash flow forecasting and fraud detection. More recently, I've been diving deep into the world of Generative AI, building enterprise-grade solutions with RAG architectures and fine-tuning LLMs. This journey has given me hands-on experience with MLOps, ensuring our solutions are not just innovative, but also scalable and reliable. Beyond my day-to-day work, I'm an active member of the tech community. You'll often find me at tech events, soaking up knowledge about the latest trends in AI.

Experience

2 yrs 8 mos

Total Experience

7 mos

Average Tenure

1 yr 8 mos

Current Experience

Arya.ai

Data Scientist

Sep 2024 – Present · 1 yr 8 mos · India · On-site

Architected Cash Flow Forecasting solutions for a global investment bank using ARIMA, LSTM, and XGBoost with scenario-based modeling, achieving a 20–25% improvement in forecast accuracy.
Built and scaled Bank Statement Analyzer APIs supporting 18 countries, processing 1M+ documents per month with 98% extraction accuracy, enabling high-volume financial document analysis.
Engineered AI-driven KYC automation systems using deep learning for Aadhaar, PAN, and Passport processing, addressing document edge cases in production and supporting adoption across 85% of Indian insurance firms.
Built and deployed end-to-end LLM applications using LangChain, FAISS, and GPT-based models for intelligent document processing, achieving 95% accuracy in automated data extraction and validation.
Developed ML-based fraud detection systems for real-time transaction monitoring in a bus ticketing platform, identifying anomalous transactions with high precision.
Delivered enterprise HR chatbots, fine-tuned on internal policy documents, integrated with internal APIs, and hosted on Google Cloud Platform (GCP) for secure enterprise use.
Presented AI solutions to global clients, conducting technical demos and webinars to showcase API Marketplace integrations and measurable efficiency gains.

Python (Programming Language)Machine LearningArtificial Intelligence (AI)Large Language Models (LLM)Communication

Atomic loops

Machine Learning Engineer

Jul 2024 – Aug 2024 · 1 mo · Pune, Maharashtra, India · Remote

Fine-tuned LLaMA 2 for question-answering tasks using LoRA and QLoRA, enabling efficient model adaptation and quantization.
Developed a Retrieval-Augmented Generation (RAG) pipeline to extract and retrieve structured information from PDFs for an industry-specific AI solution.

Python (Programming Language)Machine Learning

Buildspace

Project Intern

Jun 2024 – Jul 2024 · 1 mo

Genie ai

Intern

Apr 2024 – Jun 2024 · 2 mos · Canada · Remote

Optimized the AlbisAI chatbot using LangChain by refining prompt templates, improving accuracy in PDF-based document retrieval.
Enhanced LLM-driven document understanding workflows to support more reliable question-answering over unstructured data.

Artificial Intelligence (AI)Large Language Models (LLM)

Tech mahindra

Intern

Jul 2023 – Dec 2023 · 5 mos · Pune, Maharashtra, India · On-site

Led exploratory data analysis (EDA) and automated data pipeline development for the INDUS Project, a large language model, supporting training across 37 dialects with careful handling of low-resource data scenarios.
Implemented voice morphing using Tortoise TTS, applying deep learning techniques for personalized and natural speech synthesis.

CommunicationTeamworkArtificial Intelligence (AI)Large Language Models (LLM)Machine LearningSoftware Development+1

Viral fission

Campus Ambassador

Dec 2022 – Apr 2023 · 4 mos · Mumbai, Maharashtra, India · Hybrid

Supported campus-level marketing initiatives by promoting campaigns and increasing student engagement across the college community.
Acted as a point of contact between the organization and students to drive awareness and participation.

Teach for india

Nonprofit

Nov 2022 – Jun 2023 · 7 mos

Designed and implemented an innovative educational program while teaching at Teach For India, resulting in a remarkable 56% improvement in students exam performance.
Organized interactive sessions and events to promote student engagement, fostering a positive and dynamic learning atmosphere.
Demonstrated the ability to lead and communicate effectively in diverse and collaborative environments.

Analytical SkillsProblem SolvingMathematicsStatistical Data AnalysisCOM

Ieee viit student branch

Event Coordinator

Sep 2022 – Mar 2023 · 6 mos

Coordinated the planning and execution of a college-level hackathon, managing participant onboarding, scheduling, and on-ground logistics.
Collaborated with cross-functional student teams to ensure smooth event operations and attendee experience.

Iot forum

Head of Sponsorship

Aug 2021 – Nov 2021 · 3 mos

Supported sponsorship initiatives by assisting in communication with potential sponsors and participating in partnership discussions.
Coordinated internally to align sponsorship requirements with event planning and execution.

Symposium viit

Marketing Team

Jun 2021 – Nov 2021 · 5 mos

Contributed to marketing efforts by designing posters and assisting in content creation for event promotions.
Supported campaign planning to improve reach and engagement across student audiences.