Data Analytics And Ml Engineer
CurrentRole & Responsibilities: 1.Problem Formulation: Define and formulate business problems as data-driven questions and hypotheses. 2.Data Collection: Gather relevant data from various sources to address specific business challenges. 3.Data Cleaning and processing: Ensure data quality by cleaning and processing data, handling missing values and errors. 4.Exploratory Data Analysis (EDA): Explore data through statistical analysis and visualization to uncover patterns and trends. 5.Reporting: Generate reports and dashboards to communicate insights using tools like Tableau or Power BI. 6.Business Intelligence: Provide actionable insights to support business decision-making based on data analysis. 7.Querying Databases: Write SQL queries to extract and manipulate data from databases. 8.Model Selection and Development: Choosing appropriate machine learning algorithms and architectures based on the problem requirements, develop, train, and optimize machine learning models using libraries like scikit-learn. 9.Model Evaluation and Validation: Assessing the performance of machine learning models using appropriate evaluation metrics and cross-validation techniques to ensure that models generated is accurately predicting to different scenarios.