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Contact

📞 +91 7909046614

✉️ sanskaarprivate@gmail.com

📍 Jamshedpur**, India**

🌐 Linked In

💻 GItHub

Interests

🎧 Music

📽️ Cinema

✒️ Writing

Languages

🇬🇧 English

🇮🇳 Hindi (Native)

A data analyst with a strong foundation in statistical science, a flair for creative tech, and a track record of turning messy real-world datasets into clean, actionable insights that drive decisions. With over a year of full-time industry experience and several impactful internships under my belt, I bring a rare blend of domain versatility, tool mastery, and system-level thinking.

My academic foundation in Statistics backs everything I do, from hypothesis testing, regression modeling, and time series forecasting, to advanced experimental design, optimization techniques, and quality control (Six Sigma, DMAIC, SPC). I’ve solved problems across fleet analytics, logistics, procurement, and operations, helping organizations reduce turnaround time, predict SLA breaches, and make their data work harder.

Technically, I’m fluent in Python (Pandas, NumPy, Seaborn, statsmodels), SQL (Redshift, Athena, PostgreSQL, MySQL), Power BI, Excel VBA, and QuickSight, building full-stack dashboards and data tools from scratch. Whether it’s writing SQL queries that pull multi-million row tables into insight-rich summaries, or automating Excel-based workflows for ops teams, I’m always looking for ways to bring speed, clarity, and impact. I’m also comfortable working with machine learning pipelines, multivariate analytics (PCA, Factor Analysis), and forecasting models (ARIMA, exponential smoothing), with strong model diagnostics and assumption testing at the core.

But my work doesn’t stop at data wrangling. I deeply value storytelling, I design intuitive dashboards, create stakeholder-ready reports, and translate statistical output into sharp, decision-ready visuals. From building performance scorecards for execs to designing event analytics for cultural startups, I approach every dataset with a balance of rigor and creativity.

Outside the strict realm of analytics, I’m also a creative technologist, co-founder of CrysisCulture, where I built campaign analytics, engagement funnels, and sponsorship performance reports. I also produce music (released on Spotify & Apple Music), and have worked with tools like Adobe Photoshop, Premiere Pro, Blender, and FL Studio, using design to support data, and data to enhance design.

I thrive on solving ambiguous, multi-layered problems with a structured mindset. Whether I’m forecasting delivery delays using time series models, reducing idle hours through EDA, or simply building a dashboard that makes someone’s job easier, I bring intensity, intention, and insight to the table. And most importantly.

I don’t just work with data, I understand it, respect it, and make it speak.

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Work History

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Bhawani Transport

Bhawani Transport is a high-volume logistics company operating across multiple verticals, where I led analytics initiatives spanning SLA optimization, fleet efficiency, and operational intelligence. My role covered data engineering, statistical modeling, dashboarding, and stakeholder reporting — driving measurable impact across business functions.

Data Analyst

May 2024 - May 2025

🚛 Revamped the SLA tracking system by identifying lag patterns in dispatch workflows using Python + SQL; reduced delivery delays and improved SLA adherence by 17% across 4 business verticals.
📊 Built and deployed 6+ live dashboards using Power BI and Amazon QuickSight, enabling real-time visibility into dispatch efficiency, vehicle utilization, route delays, and rgion-wise performance metrics.
🧮 Conducted EDA on 100K+ trip logs using Python (Pandas, NumPy); discovered peak-hour traffic clusters and delay trends — contributing to a 12% reduction in average turnaround time (TAT).
⚙️ Automated daily reporting workflows by integrating SQL (Redshift, PostgreSQL) queries with Excel VBA scripting; reduced manual effort by 20% and standardized report delivery to <5 minutes.
📉 Applied the DMAIC framework to isolate root causes behind SLA breaches. Used control charts, process capability indices (Cp, Cpk), and Pareto analysis to identify top 3 failure points and fix them.
📈 Designed a forecasting pipeline using regression + ARIMA time series modeling in Python to predict delivery lags, allowing pre-emptive resource allocation and cutting reactive escalations by 30%.
🧾 Developed multi-level KPI scorecards combining trip logs, driver performance, and customer feedback — integrated into monthly ops reviews across 3 regional zones.
🛠️ Unified messy datasets across dispatch records, driver rosters, GPS trackers, and customer forms using SQL and Python-based ETL scripts — creating a single source of truth for BI dashboards.
🚨 Built a Python-powered anomaly detection engine for identifying fleet-level irregularities like over-idling, route deviations, and fuel abuse — improved asset monitoring accuracy by 28%.
📣 Delivered ad hoc performance reports and deep-dive insights for senior leadership — including visual storytelling using matplotlib/seaborn and PowerPoint-ready output.
🔍 Spearheaded a rule-based anomaly flagging model for underperforming vehicles and overused routes, boosting early detection of operational bottlenecks by 25%.
💡 Initiated and led a driver feedback analytics loop — built survey dashboards, cross-referenced feedback with ops KPIs, and proposed incentive restructuring to align behavior with business goals.
🧹 Enhanced data quality by identifying nulls, schema inconsistencies, and validation gaps in 3 major data flows; implemented SQL-based validation logic and process audits to boost accuracy by 18%.

Internships

Lakhdataar Udyog

Lakhdataar Udyog is a growing e-commerce platform managing pan-India order fulfillment and vendor sourcing. I worked within the Finance & Procurement vertical to streamline backend purchase processes, vendor evaluation, and cost control mechanisms. My role focused on data-driven procurement optimization and building visibility tools for financial decision-making.

Business Analyst Trainee – Finance & Procurement

December 2023 - April 2024

Cleaned and aligned procurement data across 3 vendor tiers, reducing reconciliation errors by 28%.
Created Excel- and Power BI-based vendor dashboards to track delivery timelines and delays — improved >2-day lag detection by 14%.
Designed budget vs spend trackers across 5 major cost centers, enabling finance heads to monitor real-time burn and vendor-wise expenditure.

Ready Wheels

Ready Wheels is a tech-enabled fleet optimization startup working with IoT-powered vehicle diagnostics. I contributed to the fleet analytics division, handling sensor log parsing, anomaly detection, and backend logic support for ops dashboards.

Data Analyst Intern - Fleet Analytics

March 2023 - May 2024

Processed diagnostic logs from 200+ IoT-connected vehicles using Python, flagged high-idle clusters and reduced unproductive hours by 11%.
Used C++-style pseudo scripting to improve backend pipeline logic for automated KPI extraction.
Supported the enhancement of real-time dashboards with cleaner, pre-processed data flows.

Black Diamond Motors

Black Diamond Motors is a regional logistics provider with a focus on dispatch operations. I worked on optimizing dispatch logs, visualizing turnaround time (TAT), and implementing data automation solutions for daily ops reporting.

Data Associate Intern - Dispatch Operations

March 2022 - May 2022

Automated fuel logs across 2 states using SQL + Power BI — reduced manual entry burden by 80%.
Built a real-time TAT dashboard that flagged dispatch delays within 30 seconds of record sync.
Created Excel-triggered email alerts for outdated dispatch forms, cutting usage errors from 15% to 4%.