Manager Advanced Analytics & Data Science

Tawteen

Main Role (Overall accountability):

The Manager - Advanced Analytics & Data Science is responsible for spearheading the development and execution of advanced analytical initiatives that drive strategic business decisions. This role involves employing sophisticated analytical methods, such as machine learning, artificial intelligence, and statistical modeling, to solve complex business challenges and uncover growth opportunities. The role is pivotal in transforming raw data into strategic insights and fostering innovation through data science.

Principal Accountabilities:

1. Advanced Analytical Solutions:

• Design and develop complex analytical models to address intricate business problems.
• Implement machine learning algorithms and AI techniques to predict trends and automate processes.
• Conduct exploratory data analysis and hypothesis testing to generate actionable insights.

2. Innovative Data Science Applications:

• Drive the adoption of cutting-edge data science methodologies and technologies.
• Explore and implement new analytical tools and platforms to enhance capabilities.
• Lead experimental projects to innovate and improve existing processes.

3. Predictive and Prescriptive Analytics:

• Develop predictive models to forecast future business outcomes and identify opportunities.
• Create prescriptive analytics frameworks to recommend actions based on data insights.
• Monitor model performance and iterate to maintain accuracy and relevance.

4. Strategic Data Initiatives:

• Lead data-driven projects that align with the organization s strategic goals.
• Collaborate with senior leadership to define data strategy and priorities.
• Identify and prioritize high-impact analytical opportunities.

5. Data Governance and Quality:

• Ensure the integrity, accuracy, and consistency of analytical data.
• Implement data governance best practices and standards.
• Oversee data cleaning, transformation, and integration processes.

6. Team Leadership and Development:

• Lead, mentor, and grow a team of data scientists and advanced analysts.
• Foster a culture of continuous learning and innovation within the team.
• Manage resource allocation, project timelines, and deliverables.

Knowledge, Skills & Competencies Required:

Extensive knowledge of advanced analytics tools and programming languages (e.g., Python, R, Julia). Proficiency in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Keras).

Proficient in programming and using SAS tools SAS EG, SAS Minor, Marketing Automation, SAS Visual Analytics, Info Maps is a huge added advantage although not mandatory.

Proficiency in data science with R programming and various R packages in enterprise environment (e.g. POSIT Workbench, Connect, Package Manager) will be added advantage.

Strong understanding of AI, deep learning, and natural language processing (NLP), Advanced classical analytics (e.g. multivariate segmentation models, credit scorings, propensity models, price sensitivity models). Proficiency in various techniques, e.g. decision trees, clustering, logistic regressions etc.

Advanced understanding of ML techniques & algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.

Applied knowledge of statistics methods, such as distributions, statistical testing, regression, etc.

Superior understanding of personal/corporate/treasury businesses and products and services