Team Management
- Manage a team of data scientists, providing guidance and direction on projects and tasks.
- Work with the data scientist team to define models to be created and implemented together with the approach for implementing them and monitor for accuracy, integrity, and robustness.
- Set performance goals and objectives for team members, and regularly assess progress towards achieving them.
- Provide technical leadership as well as mentorship and coaching to team members / data scientists and new team members and supporting their growth and professional development.
- Build a positive and collaborative team culture that fosters innovation, creativity, and continuous learning.
- Participate in strategic & tactical planning discussions.
- Develop, plan, and prioritize data projects (including timelines, deliverables, and milestones), ensure they are communicated to stakeholders and team members and delegate assigned roles and responsibilities for execution, weighing business and technical trade-offs as required.
- Lead data science projects from start to finish, ensuring they are completed on time, within budget, and to the required quality standards.
- Manage project risks and issues and develop mitigation strategies as necessary.
- Collaborate with cross-functional teams to ensure that data science projects are aligned with business objectives and priorities.
- Work with business stakeholders including senior leaders, data, and software teams to identify business requirements and model and frame business scenarios that deliver impact on business processes and/or decisions.
- Work closely with data and software teams to shape and enable deployment of fit-for-purpose, robust solutions that will scale across ecosystem.
- Identify and manage data development challenges, offer suggestions, and deploy appropriate solutions.
- Prepare and deliver business reviews to the senior management team regarding progress and roadblocks.
- Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
- Stay up to date with the latest data science methodologies and best practices, and ensure they are being applied effectively within the team to ensure the latest technology, techniques and methods are always applied.
- Lead the development and implementation of new data science methodologies and techniques that can improve business outcomes.
- Make recommendations for new metrics, techniques, and strategies to improve team performance and measurement in the future.
- Provide guidance and oversight on data cleaning, pre-processing, feature engineering, and model selection and evaluation.
- Ensure that data science models are robust, accurate, and scalable, and that they can be easily integrated into business processes and systems.
- Define the data elements and data structure that teams should leverage to enable analytical and reporting capabilities for the business development team.
- Enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format.
- Be a thought leader and forward thinker, anticipating obstacles to success and helping avoid common failure modes.
- Design and influence operational best practices for reporting and analytics to enable the team to scale.
- Ensure that data science solutions are scalable, secure, and compliant with data privacy regulations
- Build strong relationships with stakeholders across the organization, including business leaders, data analysts, IT teams, and other data science teams.
- Collaborate with IT teams to ensure that data science solutions are integrated with existing IT systems and infrastructure.
- Communicate complex data science concepts and solutions to non-technical stakeholders in a clear and concise manner.
- Work closely with business leaders to understand their needs and priorities and ensure that data science projects are aligned with them.
- Provide regular updates and reports on data science projects to stakeholders, and ensure that they are informed of progress, risks, and issues.
- Communicate and present analytical findings, results, and reports to senior stakeholders, using data visualization techniques to tell compelling stories, while tying progress to enterprise goals.
- Bachelors or masters degree in a relevant field such as computer science, data science, statistics, or mathematics, Information Technology, Information Systems, or a related field (essential).
- +6 years experience in a data science or similar role, with a minimum of 2 years in a leadership or management position within a fast-paced environment (essential).
- Solid experience applying machine learning, deep learning, data mining, modelling and mathematical and/or statistical concepts and methodology to support strategic business objectives. (preferred).
- Expertise in SQL, Python, and data science toolkits (essential).
- Experience leading and developing others whilst taking ownership for project outcomes (essential).
- Experience delivering project outcomes using design thinking, lean and agile principles (essential).
- Strong proficiency in MS Office 365 with advanced Excel skills (essential).
- Experience in a retail environment (highly desired).
- A data expert with the skill of practicing the art of Data Science. Solves complex data problems to answer business questions using their expertise in scientific disciplines.
- Critical thinker with strong quantitative skills Able to collect, organize and assimilate disparate, multiple, and complex pieces of data to draw sound conclusions and arrive at optimal solutions.
- Strong technical aptitude with a passion and excitement for data, new technologies and solutions and its range of possibilities, applications, and value for the business.
- High level of self-motivation and drive to meet and exceed on goals and expectations and engage and energize others to deliver on expectations. Comfortable taking decisions and dealing with a range of problem-solving challenges independently.
- Leadership skills - Natural leader with the ability to easily establish trust-based relationships.
- Coaches and mentors others to deliver end-to-end business solutions in a collaborative and professional manner.
- Detailed, organized and quality focused Has an affinity for detail, structure and efficiency, balancing planning, and execution. Is diligent and vigilantly watches over work processes, tasks, and outputs to ensure accuracy while independently actioning and correcting any quality concerns.
- Strong communicator and presenter Inspire commitment. Is able to confidently explain and simply complex technical concepts and their real-world advantages/disadvantages to a diverse business audience. Able to compile visual reports that tells a concise and compelling story.
- Collaborative partner - Works effectively across functions and as part of a multi-disciplinary team. Is collaborative and able to build sound, professional relationships with internal and external stakeholders.
- Ability to work under pressure and under tight time constraints, efficiently prioritizing workloads, balancing multiple, competing priorities, and managing time effectively in a high-volume, fast- moving environment. Enjoys challenging work and has the proven ability to effectively adapt to and manage change.
- Is curious and adaptable, finds agile and rapid ways of answering business questions and implementing solutions fast. Plays an integral role in building Shoprites data science muscle, constantly finding ways to leverage opportunities.
