Analyses and interprets complex data to help organizations make informed decisions. Uses techniques from statistics, machine learning, and data analysis to extract insights from both structured and unstructured data. The role involves cleaning, organizing, and visualizing data, as well as building predictive models and algorithms. Key Responsibilities: Data Collection and Cleaning : Collect data from various sources and ensure its quality. Clean and preprocess data, handling missing or incorrect values. Data Analysis and Insights : Analyze data to find trends and patterns. Provide actionable insights and recommendations for the business. Machine Learning and Predictive Modeling : Build and deploy machine learning models. Train and optimize models for better accuracy. Data Visualization and Reporting : Create clear visualizations to present data findings. Develop reports and dashboards for stakeholders. Collaboration and Communication : Work with teams to understand their data needs. Communicate technical results to non-technical stakeholders. Model Monitoring and Maintenance : Monitor model performance regularly. Make adjustments to improve accuracy. Skills Required: Proficiency in Python, R, or SQL. Expertise in data manipulation (e.g., Pandas, NumPy). Strong foundation in statistics and probability. Experience with data visualization tools. Familiarity with cloud platforms (e.g., AWS, Google Cloud). Understanding of data modelling, warehousing, and ETL processes. Ability to work with unstructured data (e.g., text, images). Educational Background: Bachelors degree in data science, Computer Science, Statistics, Mathematics, or a related field. Masters or Ph.D. in a relevant field is preferred. 2 years experience