Komal Sathe

Experience

• 

  Microsoft Partner

  Jan 2023 - Mar 2023

  Predictive Modelling Intern

  During my internship at Microsoft Partner, I gained hands-on experience in data manipulation, analysis, visualization, and predictive modeling, leveraging Python and machine learning techniques to drive data-driven insights and decision-making. This role provided me with a comprehensive understanding of the end-to-end data science workflow and honed my technical and analytical skills.My primary responsibilities involved data manipulation and preprocessing. I utilized Python libraries such as Pandas and NumPy to clean, transform, and prepare large datasets for analysis. This included handling missing values, outlier detection, and feature engineering to enhance data quality and suitability for modeling.In the data analysis phase, I employed statistical techniques and Python libraries like SciPy and StatsModels to conduct in-depth analyses. I performed exploratory data analysis (EDA) to identify trends, correlations, and patterns within the data, which informed the development of predictive models and strategic recommendations.Data visualization was another critical aspect of my role. I created informative and visually appealing dashboards and charts using libraries such as Matplotlib and Seaborn, as well as interactive visualizations with Plotly. These visualizations facilitated clear communication of complex data insights and model results to stakeholders, enabling them to make informed decisions based on the presented data.Overall, this internship provided me with invaluable experience in leveraging Python and machine learning techniques for data manipulation, analysis, and visualization. It reinforced my passion for data science and equipped me with the skills to tackle complex data challenges and contribute to impactful projects. Show less

• 

  UBS

  Jul 2023 - now

  Quantitative Analysis Intern

  During my internship at UBS Business Solutions, I had the opportunity to apply my academic knowledge in a practical setting, focusing on model development using R software and advanced statistical techniques. This role allowed me to delve deeply into the world of data science, leveraging my skills to develop predictive models that drive strategic decision-making.One of my primary responsibilities was to analyze complex datasets, using R to clean, preprocess, and visualize data. I employed various statistical methods, including regression analysis and hypothesis testing, to identify trends, correlations, and insights that were crucial for model development. My work involved designing and implementing predictive models to forecast outcomes and trends, which required a solid understanding of machine learning algorithms and statistical theories.In addition to model development, I conducted rigorous validation and performance evaluation of the models to ensure their accuracy and robustness. This involved splitting data into training and test sets, performing cross-validation, and assessing model performance using metrics such as precision, recall, and ROC curves. My ability to interpret these metrics and refine the models based on performance feedback was crucial in delivering high-quality results.Throughout the internship, I collaborated closely with cross-functional teams, including data engineers and business analysts, to integrate the predictive models into the company's existing systems and processes. This collaborative approach ensured that the models were effectively utilized and that their outputs aligned with the company’s strategic goals.Overall, this internship provided me with invaluable hands-on experience in applying statistical techniques and R programming to real-world problems. It enhanced my skills in data analysis, model development, and communication, and reinforced my passion for leveraging data to drive meaningful outcomes. Show less