- Lead, mentor, and develop a team of data scientists. Oversee the recruitment, training, and performance evaluation of team members.
- Manage data science projects from inception to completion. Ensure projects are delivered on time, within scope, and within budget.
- Coordinate with cross-functional teams to ensure project alignment and success. Communicate findings and insights effectively to stakeholders at all levels.
- Oversee the development and implementation of advanced analytics models and machine learning algorithms.
- Lead the development and deployment of predictive models to forecast trends, customer behavior, and other key business metrics.
- Utilize advanced predictive techniques, such as regression analysis, time series forecasting, and neural networks, to solve complex business problems.
- Design and implement predictive analytics solutions to identify future trends and opportunities.
- Develop and validate predictive models to improve business outcomes such as sales forecasting, demand planning, and customer segmentation.
- Provide strategic insights and recommendations to senior management based on data analysis.
- Develop and maintain dashboards and reporting systems to monitor key
performance indicators. - Establish and enforce data governance policies and best practices. Ensure data privacy and security compliance across all data initiatives.
MINIMUM REQUIREMENTS
- Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field. A Master’s degree or PhD is highly preferred.
- Minimum of 5 years of experience in data science, with at least 2 years in a
leadership or managerial role. - Proven track record of successfully managing data science projects and teams, preferably in the Food and Beverage industry.
- Extensive experience with data analysis and machine learning tools (e.g., SQL, R, Python).
- Deep understanding of statistical analysis, machine learning, and predictive
modeling. - Proven expertise in developing and deploying predictive models using techniques such as regression analysis, time series forecasting, and neural networks.
- Proficiency in data visualization tools (e.g., Tableau, Power BI). Familiarity with big data technologies and cloud computing platforms (e.g., AWS, Azure, Google Cloud) is a plus.
- Advanced certifications in data science or related fields.
