Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
Proven experience as a Data Scientist or similar role, with a strong portfolio of projects demonstrating expertise in data analysis, machine learning, and predictive modeling.
Proficiency in programming languages such as Python, R, and SQL, as well as familiarity with relevant libraries and frameworks (e.g., Pandas, NumPy, scikit-learn).
Experience working with big data technologies and cloud computing platforms (e.g., Hadoop, Spark, AWS, Azure) is a plus.
Knowledge of data visualization tools and techniques (e.g., Matplotlib, Seaborn, PowerBI) for creating insightful and impactful visualizations.
Create visually compelling and informative data visualizations to communicate findings and insights to stakeholders.
Apply statistical analysis techniques and machine learning algorithms to solve real-world problems and extract meaningful patterns from data.
Develop predictive models and algorithms to support business objectives, such as customer segmentation, demand forecasting, and recommendation systems.
Collaborate with cross-functional teams including data engineers, business analysts, and product managers to understand business requirements and develop data-driven solutions.
Stay updated with the latest advancements in data science, machine learning, and AI technologies, and apply them to enhance our analytical capabilities.
Contribute to the development and maintenance of data infrastructure, including data pipelines, data warehouses, and cloud-based storage solutions.
Participate in experimental design, A/B testing, and optimization efforts to continuously improve the performance of our products and services.
Provide mentorship and guidance to junior team members, sharing best practices and fostering a culture of innovation and continuous learning.
