Skills: –
•Proficiency in Python, R, and SQL is crucial.
•Understanding of fundamental machine learning algorithms.
•Familiarity with tools like for handling large-scale datasets and distributed computing.
•Clear communication skills are essential.
•Strong problem-solving skills to tackle real-world data challenges
•Ability to collaborate with multidisciplinary teams including data engineers, business analysts.
•Knowledge of data mining techniques is required.
Roles and Responsibilities: –
•Gather and clean data from various sources, such as databases, APIs, and files.
•Visualize data using charts, graphs, and other visualization techniques to identify patterns and trend
•Experiment with different algorithms and techniques to improve model performance.
•Interpret model results and communicate findings to stakeholders.
•Participate in team meetings, brainstorming sessions, and project reviews.
•Maintain clear and concise documentation for future reference and knowledge sharing.
•Take initiative in identifying opportunities for process improvement and innovation.
•Ensure fairness, transparency, and accountability in data-driven decision-making processes.
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