Data Scientist (DBN)

• Develop and deploy Machine Learning and Artificial Intelligence models and algorithms to extract insights, predict outcomes, and optimize processes.
• Conduct in-depth data analysis, data exploration, and data preprocessing to extract valuable information from large datasets.
• Apply statistical techniques and hypothesis testing to validate findings.

• Collaborate with stakeholders to define data-driven objectives and formulate data strategies aligned with business goals.
• Identify Key Performance Indicators (KPIs) and establish data collection and measurement protocols.

• Engineer features and create data pipelines to prepare and clean data for modeling.
• Work with Data Engineering teams to ensure data availability and quality.

• Evaluate model performance and fine-tune models for improved accuracy.
• Deploy models in production environments and monitor their ongoing performance.
• Implement best practices for model version control and management.
• Ensure proven models are integrated into business processes and software products removing the requirement for human intervention to implement the model within their respective businesses.

• Collaborate with Business Analysts, Data Engineers, and domain experts to understand and address specific business problems.
• Communicate findings and insights to non-technical stakeholders in a clear and actionable manner.

• Provide leadership and mentorship to Junior Data Scientists.
• Participate in knowledge-sharing and training programs to enhance the Data Science capabilities of the team.
• Foster a collaborative and innovative work environment.

• Ensure data privacy and compliance with relevant regulations and best practices.
• Develop and enforce data security protocols.

• Master''s or Bachelors Degree in Computer Science, Data Science, or a related field.
• Relevant Certifications e.g. Certified Data Scientist etc. are a plus.

• A minimum of three years of experience in Data Science roles, including hands-on experience with Machine Learning and Statistical Analysis.
• Proficiency in Data Analysis and modelling tools and libraries e.g. Python, R.
• Strong Programming skills and knowledge of data manipulation and visualization.
• Expertise in data preprocessing, Feature Engineering, and model evaluation.

• Strong problem-solving and critical-thinking skills.
• Ability to work in a fast-paced, dynamic environment.
• Strong project management and organizational skills.
• Excellent interpersonal and teamwork skills.
• Strong communication and interpersonal skills to effectively collaborate with various stakeholders.

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