Karthikeyan Rajagopal

WORK HISTORY

EDUCATION

ABOUT KARTHIKEYAN RAJAGOPAL

I\'m a data and product professional driven by a deep passion for unearthing insights from data and transforming industries. With over 4 years under my belt, I\'ve had the privilege of diving deep into diverse sectors such as eCommerce, travel, and banking. My expertise shines in crafting context-specific product recommendations, building predictive models, and turning vast amounts of data into actionable strategies.Product Manager with 5 years of experience, delivering products and insights to global clients across banking, fintech, travel, and sports industries. Expert in transforming complex business problems into data-driven strategies and actionable insights through machine learning, predictive modeling, analytics, and visualizations. Adept at leading cross-functional teams, defining product strategy, and building scalable analytics solutions that drive business performance-Programming Languages: Python, R, SQL, Java, Scala, C, C++Tools & Framework: Tableau, PowerBI, Plotly, Streamlit, Redshift, SageMaker, QuickSight, BigQuery, Looker, Vertex AI, Dataiku, Snowflake, Spark, Hive, Hadoop, Airflow, Tableau, Power BI, DBT, GitHub, MS Excel, FlaskCloud Computing: AWS, Google Cloud Platform (GCP), Microsoft AzureDatabases: MySQL, PostgreSQL, MongoDB, CassandraLibraries: Pandas, Numpy, Matplotlib, Seaborn, scikit-learn(sklearn), TensorFlow, PySpark, PyTorch, Spacy, Huggingface, LangChainMachine Learning Algorithms: Regression Models (Linear, Logistic, Lasso and Ridge), Decision Trees, Random Forest, Gradient Boosting, XGBoost, LightGBM, Naïve Bayes, SVM, Clustering, DBSCAN, K-Means, NLP, Deep Learning, BERT, Neural Networks, Large Language Models(LLMs)Statistical Analysis and Model Interpretability: Descriptive & Inferential Statistics, Hypothesis Testing, Univariate and Multi-Variate Analysis, Weight of Evidence (WoE), Information Value (IV), Principal Component Analysis (PCA), Shapely ValuesTechnical Skills: Machine Learning, Natural Language Processing, Recommender Systems, Exploratory Data Analysis (EDA), Data visualization, Statistics, Databases, Forecasting, A/B testing, Causal Inference, Bayesian Inference, Business Analysis