Data Science Manager

Roles and responsibilities

As a Senior Data Science Director, you will be responsible for leading and oversee the strategic direction, management, and execution of data science initiatives across the organization.

This role involves driving innovation, leveraging advanced analytics, and building machine learning models to solve complex business problems. The successful candidate will partner with cross-functional teams, ensure alignment with business goals, and deliver data-driven Data Science Solutions that impact key decision-making processes. This leader will also foster a data-driven culture and scale the organization's data science capabilities.

Role Scope:

Data Science Strategy & Project Management

• Develop and execute the data science roadmap in alignment with organizational strategy, ensuring project prioritization and resource allocation.
• Establish comprehensive data science project plans, incorporating methodologies such as time-series analysis, hypothesis testing, and causal inference.
• Supervise ongoing projects to ensure the application of best practices in data science, ensuring timely and accurate delivery of insights and recommendations.
• Identify opportunities for data innovation and provide leadership in emerging data science methods.

Leadership in Advanced Data Science Projects

• Oversee the full lifecycle of data science projects, from ideation and data collection to data cleaning, model development, and results validation.
• Collaborate with business owners to define project goals and ensure alignment with business needs.
• Ensure the quality and integrity of data science outputs, implementing rigorous validation procedures to maintain accuracy and reliability.

Data Architecture & Metrics Development

• Develop a deep understanding of organizational data structures and metrics, advocating for improvements in data infrastructure and analytics capabilities.
• Drive collaboration with data technology and data intelligence teams to enhance data platforms and ensure seamless integration of analytics tools.

Strategic Decision-Making Support

• Support the Executive Director in transforming business decision-making through the application of data science insights.
• Translate complex data findings into actionable recommendations that deliver measurable value to the enterprise and foster revenue growth.
• Leverage data science to identify business trends and opportunities, enabling proactive strategic decisions.

Desired candidate profile

• Lead and mentor a team of data scientists, fostering a culture of innovation, learning, and inclusivity.
• Provide coaching and constructive feedback to team members to encourage professional growth and development.
• Drive team performance by setting clear goals, providing ongoing support, and maintaining a high-performance work environment.

Cross-Functional Collaboration & Stakeholder Management

• Build strong relationships across departments, particularly with counterparts in data technology and business units, to drive collaboration and alignment of data science initiatives.
• Facilitate cross-functional learning by sharing insights and best practices with other teams.
• Maintain relationships with external partners and vendors, identifying opportunities for collaboration to further data science capabilities.

Data Governance & Ethics

• Ensure adherence to data protection regulations and ethical guidelines in all data science activities.

Requirements:

• Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or any relevant field or equivalent work experience accepted
• 10+ years of overall experience in Data and Analytics
• 8+ years of relevant experience within particular area of expertise in Data Science, Machine Learning, AI etc
• Strong problem-solving skills with an emphasis on product development
• Deep knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
• Profound understanding of the current and future technology trends and their inter-operability, especially business analytics and decision-making methodologies
• Experience in manipulating, processing and extracting value from large disconnected datasets
• Excellent ability to collaborate effectively with different teams
• Excellent written and verbal communication skills
• Proficiency in programming with Python, R, or similar programming language
• Proficiency in Microsoft Azure stack and the corresponding data analytic and data management tools such as DataBricks, AzureML, ADF, ADLS etc.
• Proficiency in distributed databases and query languages such as SQL or HQL (Snowflake)