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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