Prajakta Satbhai
Junior Associate Statistics @Upthink
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WORK HISTORY
Junior Associate Statistics @Upthink
Pune, IN
Currently working as a Junior Associate – Statistics, supporting online higher-education courses by providing accurate, timely, and conceptually clear assistance to students.• Respond to student queries related to statistics and quantitative concepts, delivering clear explanations through real-time and offline chat-based tutoring.• Assist in grading and reviewing student submissions, ensuring accuracy, consistency, and adherence to academic rubrics.• Provide constructive, actionable feedback to help learners strengthen their understanding of foundational statistical methods.• Support instructors and teaching assistants by managing course-related administrative tasks within the Learning Management System (LMS).• Maintain high standards of subject quality, attention to detail, and turnaround time while handling multiple tasks across shifts.• Contribute to internal academic and operational projects aimed at improving course delivery and learner experience.
EDUCATION
JAI HIND ET'S ZULAL BHILAJIRAO PATIL COLLEGE, DHULE.
Bachelor's degree, Statistics
North Maharashtra University
Master of science , Indusrial Statistics
ABOUT PRAJAKTA SATBHAI
I am an AI-focused Statistics postgraduate sitting at the intersection of Generative AI Training, AI Safety, and Quantitative Reasoning. With hands-on experience in Human-in-the-Loop (HITL) evaluation for global platforms like Turing, I specialize in ensuring that the next generation of Large Language Models (LLMs) is factually accurate, ethically aligned, and instruction-compliant.My recent work has centered on the shift toward Agentic AI, where I design and evaluate complex instruction-following scenarios, multi-step decision-making workflows, and tool-use behaviors. I am particularly skilled in Hallucination Mitigation and Multimodal AI Evaluation, having worked on projects that require identifying factual gaps in model outputs across both text and visual software interfaces. As a Statistics professional, I leverage my academic rigor to enhance Mathematical Correctness in AI. This includes supporting Supervised Fine-Tuning (SFT) and RLHF processes by distilling advanced mathematical concepts into structured, high-quality annotations using LaTeX. Currently, at UpThink, I translate my passion for logic and clarity into Academic Guidance, helping students master statistical concepts through structured, step-by-step reasoning—a pedagogical skill that directly informs my approach to Prompt Engineering and model behavior alignment. Core Expertise- AI Training & Safety: RLHF, SFT, Model Alignment, Red Teaming, and Hallucination Mitigation- LLM & Agent Evaluation: Instruction-Following, Multi-step Logic, and Multimodal Quality Assurance- Statistical Analysis: Quantitative Reasoning, Bio-statistics, and Predictive Analytics (Python, R, SPSS, SQL)- Technical Documentation: LaTeX, Tableau, and BI Tools. I am driven by the challenge of making AI systems more reliable, safe, and logically sound. Let’s connect to discuss the future of Responsible AI and Data-Driven Evaluation.
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