Data Scientist & AI Engineer

YOGESHGAVHANE

› Python · LangGraph · Prompt Engineering · Power BI · SQL

Results-driven Data Scientist building AI-powered analytics, agentic LLM workflows, and intelligent automation. Transforming raw datasets into strategic insight through EDA automation, LangGraph orchestration, and precision prompt engineering.

Agentic AI LangGraph Prompt Engineering EDA Automation Power BI Python SQL Streamlit

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DATA · AI

EDA.run() LangGraph Python SQL

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Technical Arsenal 01/04

CORE SKILLS

🐍

Python

Advanced data wrangling, pipeline automation, and ML workflows using Pandas, NumPy, Streamlit, and Plotly. The backbone of every analytical solution.

PROFICIENCY92%

📊

Statistics & EDA

Descriptive and inferential statistics, hypothesis testing, distribution analysis, outlier detection, and correlation mapping for data-driven decisions.

PROFICIENCY90%

🗃️

SQL

Complex joins, CTEs, window functions, aggregation pipelines, and performance-tuned queries for business intelligence and data extraction.

PROFICIENCY85%

📈

Power BI & Excel

Interactive dashboards, DAX formulas, data modeling, and executive-ready visual reports that communicate insight with clarity and precision.

PROFICIENCY88%

🤖

LangGraph

Designing stateful multi-agent systems with conditional routing, memory persistence, tool-calling nodes, and complex agentic orchestration graphs.

PROFICIENCY80%

💬

Prompt Engineering

Chain-of-thought reasoning, few-shot examples, system prompt architecture, structured output extraction, and reliable LLM behavior design.

PROFICIENCY87%

Featured Work 02/04

DATA SCIENCE PROJECT

Featured Project

AUTOMATED EDA TOOL

Built a full-stack Automated Exploratory Data Analysis tool that dramatically streamlines the process of understanding and visualizing any dataset. Users simply upload a CSV or Excel file and the application instantly delivers comprehensive analytical insights — no coding required.

PythonStreamlitPlotlyPandasNumPy

Impact: Significantly reduces manual effort in exploratory analysis — enabling both data analysts and non-technical stakeholders to gain instant insights without writing a single line of code.

📊 Dataset Intelligence

Auto-displays shape, data types, missing value counts, and full summary statistics the moment a file is uploaded.

📉 Dynamic Visualizations

Generates histograms, scatter plots, box plots, and correlation heatmaps automatically using Plotly for interactive charts.

🔍 Data Quality Audit

Highlights data quality issues, potential outliers, and anomaly patterns with intelligent flagging and automated alerts.

📄 Report Export

Exports professional summary reports in both PDF and HTML formats, ready for stakeholder presentation instantly.

AI Engineering 03/04

AGENTIC AI & LLM
ENGINEERING

Specializing in the frontier of AI engineering — designing multi-agent systems where LLMs don't just answer questions but autonomously plan, execute, and iterate toward complex goals.

LangGraph enables stateful graph-based orchestration where agents coordinate tool use, memory, and decision branching with precision. Combined with surgical prompt engineering, these systems behave reliably and predictably at production scale.

graph = StateGraph(AgentState)
graph.add_node("planner", plan_step)
graph.add_node("executor", execute_step)
graph.add_node("critic", critique_step)

graph.add_conditional_edges(
  "critic", should_continue,
  {"continue": "planner",
   "end": END}
)
// Stateful agentic loop

ORCHESTRATION

🕸️

LangGraph Workflows

Building complex stateful agent graphs with conditional routing, parallel execution branches, and persistent memory across agent steps.

StateGraph architecture design
Conditional edge routing
Tool-calling agent nodes
Memory & checkpointing

CORE EXPERTISE

🧠

Prompt Engineering

Crafting precision prompts that produce reliable, structured, hallucination-resistant outputs from large language models across diverse task domains.

Chain-of-thought prompting
Few-shot & zero-shot design
Structured JSON extraction
System prompt architecture

AI ANALYTICS

⚡

AI-Powered Analytics

Integrating LLMs into data pipelines to enable natural language queries, automated insight generation, and intelligent anomaly reporting at scale.

LLM-driven EDA insights
NL to SQL generation
Auto report narration
Anomaly explanation agents

Academic Background 04/04

EDUCATION & LEARNING

🎓

Bachelor of Business Administration

Computer Applications

CURRENTLY ENROLLED

DEGREE

BBA in Computer ApplicationsBusiness Administration with Computing focus

STATUS

Currently PursuingActively enrolled and progressing

LANGUAGES

English · Hindi · MarathiTrilingual communicator

CONTACT

yogeshgavhane465@gmail.com+91 9130625154

SELF-DIRECTED FOCUS AREAS

Data ScienceMachine LearningLLM Engineering LangGraphPrompt EngineeringAgentic AI Power BISQL AnalyticsEDA Automation