Overview

Manager, Data Control & Data Science, spearhead data-driven initiatives by leading and developing a high-performing team of data Lakehouse and big query for analysts, be responsible for shaping and implementing NLG data strategy, ensuring data quality and security, and overseeing the development and deployment of advanced analytics solutions to drive business insights and decision-making.

Responsibility

1. Data Control & Data Science

• Data Strategy & Architecture: Define and implement a robust data strategy aligned with business objectives, including data collection, storage, integration, and governance.
• Data Warehousing & Lakehouse: Oversee the design, development, and maintenance of data warehousing and lake house solutions on AWS or Google Cloud, ensuring scalability, performance, and data integrity.
• Data Modeling & Governance: Establish and enforce data modeling standards, best practices, and governance frameworks to ensure data quality, consistency, and compliance.
• Advanced Analytics & Insights: Lead the development and deployment of advanced analytics models, including data mining, big data analysis, and machine learning, to uncover actionable insights and drive business value.
• Stakeholder Collaboration: Partner with business stakeholders to understand their data needs and translate them into actionable data science projects and solutions. Communicate complex technical findings in a clear and concise manner to both technical and non-technical audiences.
• Technology & Innovation: Continuously evaluate and adopt cutting-edge technologies in the data science and cloud computing domains to maintain a competitive advantage.

2. Digital Transformation Projects:

• Technology & Innovation:
• Continuously evaluate and adopt cutting-edge technologies in the data science, cloud computing, and digital transformation domains to ensure the company stays ahead of the curve.
• Drive the implementation of innovative data-driven solutions that enable new business models, enhance customer experiences, and improve operational efficiency.

3. Data Analytics & Insights for Digital Transformation:

• Lead the development and deployment of advanced Data analytics models, including data mining, big data analysis, and machine learning, to support digital transformation initiatives.
• Identify key performance indicators (KPIs) and develop dashboards to track and measure the impact of digital transformation efforts.
• Provide insights and recommendations to guide strategic decision-making and optimize business processes.

4. Change Management:

• Develop and manage a centralized change management process for Data initiatives.
• Ensure all changes are thoroughly tested, documented, and communicated to stakeholders.
• Monitor and control change requests to minimize disruption data structure and ensure successful implementation.
• Conduct change impact assessments and develop mitigation strategies.

5. Change Control:

• Establish change control procedures to manage Data changes effectively.
• Ensure changes are aligned with business objectives and do not compromise security or compliance.
• Maintain a change control log and ensure proper documentation for all changes.
• Conduct post-implementation reviews to assess the success of changes and identify areas for improvement.

6. Data Modeling & Governance:

• Establish and enforce data modeling standards, best practices, and governance frameworks to ensure data quality, consistency, and compliance throughout the digital transformation journey.
• Champion data-driven decision-making and promote a culture of data literacy across the organization.
• Work closely with business leaders and cross-functional teams to understand their digital transformation goals and translate them into actionable data science projects.
• Communicate complex technical findings in a clear and concise manner to both technical and non-technical stakeholders, fostering understanding and buy-in.

7. User Training and Support:

• Train end-users on how to use dashboards and interpret the data presented.
• Provide ongoing support and enhancements to dashboards based on user feedback.
• Develop documentation and training materials for dashboard users.

8. Team Management:

• Lead, mentor, and develop a high-performing IT governance and PMO team.
• Set performance goals and conduct regular performance reviews.
• Foster a collaborative and innovative team culture across all IT functions
• Provide coaching and support to team members to help them achieve their career goals.

9. Professional Development:

• Team Leadership & Development: Foster a collaborative and high-performing team culture. Provide mentorship, guidance, and opportunities for professional growth to data scientists and analysts.
• Encourage a culture of compliance, governance, and accountability within the team.
• Identify training needs and provide opportunities for skill development for all Data team members & system users.
• Stay updated on industry trends and best practices to ensure the team remains competitive and knowledgeable.

Required skills and behaviors

1. Background / Experience

• Education: Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field preferred; Bachelor's degree with significant relevant experience will be considered.
• Experience: 5+ years of hands-on experience in data science, with at least 3 years in a leadership or management role. Proven track record in managing data science projects and teams, with a focus on digital transformation initiatives.
• Technical Skills: Expert knowledge of Python, R, or SQL. Expertise in data warehousing, data lake house architectures, and data modeling. Hands-on experience with big data technologies (Hadoop, Spark), cloud platforms (AWS, GCP), and machine learning frameworks.
• Leadership & Communication: Strong leadership, communication, and interpersonal skills. Ability to foster a collaborative environment and inspire a team of data professionals.
• Problem-Solving & Analytical Skills: Exceptional analytical and problem-solving abilities. Proven track record of leveraging data to drive insights and business solutions.

2. Specific job skills

• Knowledge of cloud data warehouse, data lake house, Data cybersecurity & Governance, and emerging technologies.
• Familiarity with data privacy regulations and business risk management standards.
• Ability to work under pressure and manage multiple priorities.
• Strong attention to detail and organizational skills.
• Ability to influence and build strong relationships with stakeholders at all levels.
• Good knowhow Master data, dataset, Data Governance, Big data mining and AI

3. Competencies

• Strategic Thinking: Ability to align data science initiatives with overarching digital transformation goals and objectives.
• Adaptability: Comfortable working in a fast-paced, dynamic environment with evolving priorities.
• Passion for Data & Innovation: A genuine enthusiasm for data and its potential to transform businesses through digital technologies.

4. Mindsets & behaviors

• Strategic Planning and Organization
• Initiative
• Relationship Building
• Optimism and Open-Mindedness
• Willingness to Share and Mentor
• Design/Innovation Mindset
• Integrity, Professionalism, and Ownership (Core Values)