Senior Data Scientist

İşin təsviri

Key Responsibilities:

• Lead the design, development, and deployment of machine learning models and advanced analytics solutions to solve complex business problems.
• Collaborate with stakeholders to understand business needs, translate them into analytical requirements, and deliver actionable insights.
• Mentor and guide junior data scientists, fostering a culture of continuous learning and professional development.
• Conduct exploratory data analysis to identify patterns, trends, and opportunities for optimization.
• Develop and maintain comprehensive documentation for data science projects, including methodologies, processes, and model performance metrics.
• Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence to ensure the application of cutting-edge techniques.
• Communicate findings and recommendations to non-technical stakeholders through clear and concise presentations and reports.
• Work with engineering teams to implement scalable data pipelines and integrate models into production systems.

Qualifications:

• Bachelor’s in Data Science, Statistics, Computer Science, Mathematics, Economics or a related field.
• 3+ years of experience in data science, with a proven track record of delivering successful data-driven solutions in a business environment.
• Proficiency in programming languages such as Python, R and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).
• Strong knowledge of machine learning algorithms, statistical modeling, and data visualization techniques.
• Excellent problem-solving skills and the ability to think critically and analytically.
• Strong communication skills, with the ability to present complex concepts to technical and non-technical audiences.
• Experience in the insurance industry or a related field is a plus.

Preferred Skills:

• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with A/B testing and experimental design.
• Knowledge of natural language processing (NLP) and text analytics.
• Understanding of data privacy regulations and best practices in data security.

İşəgötürənin reytinqi

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