Open to opportunities

Neha T Mathew

@nehatmathew

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Data Analyst turning large datasets into decision-ready insights with Excel, Tableau, and ML.

India

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What I'm looking for

I’m looking for a Data Analyst role where I can own end-to-end workflows—cleaning large datasets, building Excel/Tableau dashboards, and applying ML forecasting—while partnering closely with stakeholders. I’m open to relocation and require visa sponsorship.

I’m a Data Analyst with 1+ year of industry experience, turning raw datasets into clean, decision-ready insights. I build end-to-end data workflows—collecting and cleaning 40,000+ record datasets, running EDA, engineering features, and communicating results through Excel dashboards and Tableau visualisations.

At Fertmax, I collected and cleaned multi-source shipping datasets in Pandas, standardising formats, treating missing values, and removing duplicates to create the analytical layer used by the investment team. I built Excel dashboards and performed EDA and trend analysis to decompose cyclical patterns in freight rates for recurring market intelligence relied on by investment and operations teams.

I also train time-series forecasting models (ARIMA, XGBoost) with cross-validation, improving forecast RMSE by ~18% over a prior manual baseline. By automating weekly and monthly reporting pipelines, I cut preparation time from ~3 days to under 4 hours and eliminated ~6 hours of manual analyst work per week.

My MSc work and internships reinforce how I translate stakeholder needs into structured outputs: at Worley India I standardised 50,000+ rows and built FastAPI + SQLAlchemy pipelines reducing manual prep effort by ~30%, and at Cochin Shipyard I designed Tableau dashboards that reduced root-cause analysis time by ~40%. I enjoy making complex analysis clear and actionable for technical and non-technical teams.

Experience

Work history, roles, and key accomplishments

Current

Data Analyst

Current

Fertmax

Oct 2025 - Present (8 months)

Collected and cleaned multi-source shipping datasets in Pandas to create a standardized analytical layer used by the investment team. Built Excel dashboards and automated reporting pipelines, reducing stakeholders’ manual analysis by ~3 hours/week and cutting weekly/monthly prep time from ~3 days to under 4 hours.

Pandas NumPy Tableau Data Cleaning EDA ARIMA XGBoost

Data Science Intern

Worley India

Jan 2025 - Jun 2025 (5 months)

Standardized 50,000+ row engineering datasets from 5+ systems by resolving missing values, duplicates, and format inconsistencies for downstream use. Built automated pipelines (FastAPI + SQLAlchemy) to reduce manual data preparation by ~30% and delivered stakeholder-ready SQL queries and summary reports to engineering and operations teams.

fastAPI SQLAlchemy SQL Data Pipelines Data Cleaning Python Automation Data Validation

ML & Analytics Intern

Algo Analytics

Jun 2024 - Aug 2024 (2 months)

Applied EDA with RFE and PCA on 100+ feature financial time series to reduce feature count by 60% without losing predictive signal. Trained and benchmarked Random Forest and XGBoost models, with XGBoost delivering a 15% RMSE improvement and performance reporting in Matplotlib, Seaborn, and Plotly.

EDA Random Forest XGBoost Time Series Analysis Feature Engineering Benchmark Model Performance Matplotlib Plotly

IT Intern, Data Analytics

Cochin Shipyard Ltd

May 2024 - Jun 2024 (1 month)

Designed Tableau dashboards highlighting 4 procurement bottleneck patterns, reducing engineering teams’ root-cause analysis time by ~40%. Conducted EDA on 10,000+ row procurement datasets and presented findings to team leads in clear, non-technical language.

Tableau Data Visualization EDA Data Cleaning Procurement Analytics

Education

Degrees, certifications, and relevant coursework

NMIMS Mumbai

MSc (Master of Science) Statistics & Data Science, Statistics and Data Science

Grade: GPA 3.64/4.0

MSc in Statistics & Data Science with a focus on statistical modelling, machine learning, time series, Tableau, data visualisation, and Python/SQL/R. Graduated with GPA 3.64/4.0.

St. Joseph's College, Bangalore

BSc (Bachelor of Science) Computer Science, Mathematics & Statistics, Computer Science, Mathematics & Statistics

Grade: GPA 3.5/4.0

BSc in Computer Science, Mathematics & Statistics covering statistical analysis, hypothesis testing, regression, Python, and C++. Graduated with GPA 3.5/4.0.