Educational Background: Bachelors or Masters degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related discipline.
Programming Proficiency: Advanced skills in Python, with fluency in libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and Matplotlib.
Mathematical and Statistical Acumen: Solid understanding of statistical concepts, probability theory, linear algebra, and calculus.
Machine Learning Expertise: Experience with supervised and unsupervised learning techniques, model selection, and hyperparameter tuning.
Data Handling: Familiarity with SQL, noSQL databases, and data wrangling tools. Experience with data cleaning, transformation, and integration.
Data Visualization: Proficiency in creating clear, informative visualizations using Python-based or commercial tools.
Big Data Technologies (desirable): Exposure to Hadoop, Spark, or cloud-based analytics platforms such as AWS, GCP, or Azure.
Communication Skills: Ability to articulate complex technical concepts clearly and persuasively to diverse audiences.
Problem-Solving: Demonstrated ability to tackle ambiguous problems, devise creative solutions, and iterate quickly based on feedback.
Project Management: Experience managing multiple projects simultaneously, meeting deadlines, and adapting to changing priorities.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full time