Tanisha Kapoor

Data Scientist

Delhi, India 0+ yrs exp 81 · Excellent

About

Results-driven Data Science graduate with expertise in Machine Learning, Artificial Intelligence, Data Analytics, Automation, and LLM-powered applications. Proficient in Python, SQL, Scikit-learn, TensorFlow, Pandas, NumPy, and Power BI. Experienced in data preprocessing, data wrangling, feature engineering, predictive modeling, classification, regression, time series forecasting, cross-validation, model evaluation, NLP, and transforming complex datasets into actionable business insights. Passionate about building scalable, AI-driven solutions that support data-informed decision-making.

Skills & Expertise (39)

Python Intermediate

6.8/10

0.5

Years Exp

Pandas Intermediate

6.8/10

0.5

Years Exp

SQL Intermediate

6.5/10

0.5

Years Exp

Artificial Intelligence Intermediate

6.5/10

0.5

Years Exp

Machine Learning Intermediate

6.5/10

0.5

Years Exp

Data Preprocessing Intermediate

6.5/10

0.5

Years Exp

Classification Intermediate

6.0/10

0.5

Years Exp

Jupyter Notebook Intermediate

6.0/10

0.5

Years Exp

Google Collab Intermediate

6.0/10

0.5

Years Exp

Regression Intermediate

6.0/10

0.5

Years Exp

Predictive Modeling Intermediate

6.0/10

0.5

Years Exp

Feature Engineering Intermediate

6.0/10

0.5

Years Exp

Power BI Intermediate

6.0/10

0.5

Years Exp

NumPy Intermediate

6.0/10

0.5

Years Exp

scikit-learn Intermediate

6.0/10

0.5

Years Exp

Data Analytics Intermediate

5.5/10

0.5

Years Exp

TF-IDF Intermediate

5.5/10

0.5

Years Exp

NLTK Intermediate

5.5/10

0.5

Years Exp

Tokenization Intermediate

5.5/10

0.5

Years Exp

Text Classification Intermediate

5.5/10

0.5

Years Exp

Seaborn Intermediate

5.5/10

0.5

Years Exp

Matplotlib Intermediate

5.5/10

0.5

Years Exp

Excel Intermediate

5.5/10

0.5

Years Exp

MySql Intermediate

5.5/10

0.5

Years Exp

NLP Intermediate

5.5/10

0.5

Years Exp

Model Evaluation Intermediate

5.5/10

0.5

Years Exp

Cross-Validation Intermediate

5.5/10

0.5

Years Exp

Time Series Forecasting Intermediate

5.5/10

0.5

Years Exp

TensorFlow Intermediate

5.5/10

0.5

Years Exp

Tableau Intermediate

5.0/10

0.5

Years Exp

Automation Intermediate

5.0/10

0.5

Years Exp

MS Office Intermediate

5.0/10

0.5

Years Exp

LSTM Intermediate

5.0/10

0.5

Years Exp

Keras Intermediate

5.0/10

0.5

Years Exp

Generative AI Intermediate

5.0/10

0.5

Years Exp

Predictive Analytics Intermediate

5.0/10

0.5

Years Exp

Statistical Analysis Intermediate

5.0/10

0.5

Years Exp

C++ Beginner

4.0/10

0.5

Years Exp

Data Wrangling

Work Experience

Data science Intern

softnexs

Jan 2026 - Jul 2026

Worked on Artificial Intelligence and Machine learning projects. Leveraged Python, SQL, Pandas, and NumPy to perform ETL, data cleaning, preprocessing, and analysis on 10,000+ records, improving data processing efficiency by 30%. Developed predictive machine learning models achieving 80%+ prediction accuracy through feature engineering, model tuning, and evaluation.

Junior Data Scientist Intern

ShakalyaTech

Aug 2024 - Sep 2024

Wrote and optimized complex SQL queries, reducing data retrieval time by 20% for analytical workflows. Built interactive Power BI dashboards tracking 10+ KPIs, enabling faster business reporting and improving reporting efficiency by 35%. Awarded 'Best Intern – Summer Batch 2024', selected as 1 of 50 interns for outstanding technical performance, problem-solving ability, and overall contribution. Built predictive machine learning models to forecast outcomes using regression and classification algorithms, improving model accuracy through feature engineering and hyperparameter tuning. Performed data preprocessing, cleaning, and transformation on structured and unstructured datasets to ensure high-quality model inputs. Developed interactive dashboards and visualizations using Python (Matplotlib, Seaborn, Plotly) to communicate trends and business insights. Conducted exploratory data analysis (EDA) to identify patterns, correlations, and anomalies in large datasets. Implemented text segmentation and NLP preprocessing techniques, including tokenization, stop-word removal, stemming, and lemmatization, for text analytics tasks. Built text classification and segmentation pipelines using NLTK, spaCy, and scikit-learn for document and customer feedback analysis.