Lead Data Scientist

• Lead and manage data science projects from inception to completion, including goal-setting, scope definition and ensuring on-time delivery with cross team collaboration
• Collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality for enabling AI and machine learning
• Be responsible for the overall AI system design, problem framing and governance, identifying and managing risks and issues
• Design, develop and implement data science strategies that drive measurable business results
• Design experiments for the team to rapidly test ideas and assumptions, and identify future courses of action
• Use quality metrics to select machine learning models that will be deployed in the production environment
• Communicate technical findings and insights to stakeholders in a clear, easy and concise way, keeping the stakeholders in mind
• Contribute to the growth of the data science community along with promoting a culture of data literacy within the organization
• Address ethical concerns and adhere to ethical guidelines using FATTER AI (fairness, accountability, transparency, trustworthiness, explainability, responsibility)
• Work with CD4ML practices and data versioning tools

• Experience with databricks
• Experience with statistical modeling, hypothesis testing, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects
• Understanding about Gen/AI and LLMs
• Practical knowledge of Google Cloud Platform (GCP) and its core services
• Experience with R, Python or equivalent statistical/data analysis tools and can write production-ready code
• Gather and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity
• Experience with BigQuery for data modeling, querying, and performance optimization
• Develop and implement machine learning models, algorithms and predictive analytics
• Evaluate model performance using appropriate metrics and validate models
• Interpret and effectively communicate findings and insights to non-technical stakeholders
• Ensure compliance with data privacy regulations and ethical standards when handling sensitive information
• Practical knowledge of Machine Learning (ML) concepts and workflows
• Advanced English is required
• Understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders
• Are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives
• Don’t shy away from risks or conflicts, instead you take them on and skillfully manage them
• Are eager to coach, mentor and motivate others and you aspire to influence teammates
• Enjoy influencing others and always advocate for technical excellence while being open to change
• Are a proven leader with a track record of encouraging teammates in their professional development and relationships
• Cultivating strong partnerships comes naturally to you
• You understand the importance of relationship building

Learning & Development: career development is entirely up to you, supported by interactive tools, numerous development programs and teammates who want to help you grow