1. Identify valuable data sources and automate collection processes.
2. Undertake to preprocess of structured and unstructured data.
3. Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.
4. Analyze data for trends and patterns, and Interpret data with a clear objective in mind.
5. Build predictive models and machine-learning algorithms.
6. Combine models through ensemble modeling.
7. Present information using data visualization techniques.
8. Propose solutions and strategies to business challenges.
9. Collaborate with engineering and product development teams.
1. Masters or bachelor’s degree in Computer Science, statistics, applied mathematics, or related discipline.
2. Proficiency with data mining, mathematics, and statistical analysis.
3. Understanding of machine-learning and operations research.
4. Knowledge of Python, R, Power BI Tableau, SQL, and Excel, familiarity with Java or C++ is an asset.
5. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
6. Analytical mind and business acumen.
7. Problem-solving aptitude.
8. Excellent communication and presentation skills.
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