deeksha sharma

Data Analyst

Kanpur, India 0+ yrs exp 82 · Excellent

About

Detail-oriented Data Analyst with hands-on experience using SQL, Python, and Excel to analyze large-scale sensor and business datasets. Skilled in data cleaning, data validation, statistical and time-series analysis, KPI tracking, dashboard reporting, and report automation. Proven ability to turn complex, high-volume data into clear, actionable insights that support data-driven decision-making and operational efficiency.

Skills & Expertise (28)

MS Excel Intermediate

7.0/10

Years Exp

Python Intermediate

6.5/10

Years Exp

Data Cleaning & Validation Intermediate

6.5/10

Years Exp

Pandas Intermediate

6.5/10

Years Exp

SQL Intermediate

6.5/10

Years Exp

MySql Intermediate

6.0/10

Years Exp

Pivot Tables Intermediate

6.0/10

Years Exp

Dashboards Intermediate

6.0/10

Years Exp

Matplotlib Intermediate

6.0/10

Years Exp

PowerPoint Intermediate

6.0/10

Years Exp

NumPy Intermediate

6.0/10

Years Exp

Data Wrangling Intermediate

6.0/10

Years Exp

KPI Analysis Intermediate

6.0/10

Years Exp

Time-Series Analysis Intermediate

6.0/10

Years Exp

Benchmarking Intermediate

6.0/10

Years Exp

Report Automation Intermediate

6.0/10

Years Exp

Tableau Intermediate

5.0/10

Years Exp

Stakeholder Reporting Intermediate

5.0/10

Years Exp

Root-cause analysis Intermediate

5.0/10

Years Exp

Data Pipelines Intermediate

5.0/10

Years Exp

Seaborn Intermediate

5.0/10

Years Exp

Bash Beginner

4.0/10

Years Exp

Data Modeling Beginner

4.0/10

Years Exp

Version Control Beginner

4.0/10

Years Exp

Git Beginner

4.0/10

Years Exp

Postgresql Beginner

4.0/10

Years Exp

Project Management Beginner

4.0/10

Years Exp

Business process modeling Beginner

3.0/10

Years Exp

Work Experience

Data Analyst Internship

Robotoai Technologies

Jan 2025 - Nov 2025

Analyzed 100K+ remote sensor telemetry records from robotic and industrial systems using SQL, Python, and Excel to monitor machine performance and operational reliability. Queried and processed data from 5+ relational database tables using SQL/MySQL — applying joins, filtering, and aggregation to build sensor-performance metrics. Performed data cleaning and data validation with Python (Pandas, NumPy), identifying and resolving 3–5% incomplete, duplicate, or inconsistent records prior to analysis. Tracked and analyzed error rates across 25+ sensors/devices to flag high-error components and abnormal operational patterns. Conducted data-pipeline and connectivity analysis, monitoring transmission success rates and identifying ~2–4% data-delivery gaps for technical investigation. Delivered benchmarking across 5+ KPIs, comparing sensor performance against thresholds and historical baselines. Ran time-series analysis on 6+ months of sensor data to detect recurring errors, performance degradation, and trends. Built dashboards and visual reports using Pandas, Matplotlib/Seaborn, and Excel across 20+ performance metrics for reliability and pipeline health. Automated recurring data preparation and KPI reporting with SQL/Python, cutting manual reporting effort by 20–25%. Presented 10+ data-driven insights on sensor errors, connectivity, and quality deviations to guide operational decisions.