Senior Manager - Data Analytics

Role and Responsibilities

Data Analysis & Business Strategy

• Work with stakeholders across the organization to identify opportunities for leveraging data to drive business decisions.
• Mine and analyze data from company databases to support optimization and improve business strategies.
• Assess the effectiveness and accuracy of data sources and data collection methods.
• Develop and apply custom data models and algorithms to large data sets for actionable insights.
• Use predictive modeling to influence and optimize key business outcomes.

Model Development & Implementation

• Develop, operationalize, and deploy models/algorithms as structured programs or operational processes.
• Coordinate with cross-functional teams to implement models and track performance outcomes.
• Develop tools and processes to monitor model performance and ensure ongoing data accuracy.

Business Impact

• Provide actionable recommendations to business stakeholders based on model outputs.
• Drive implementation of these recommendations through changes in processes, technology, or data management practices.
• Focus areas: Primary – PSCM/VMI business; Secondary – ICS KPIs.
• Deliver measurable improvements in time or cost efficiencies post-implementation.
• Track and report business user satisfaction scores for delivered models and tools.

Quality, Safety, and Continuous Improvement

• Demonstrate commitment to Quality, Health, Safety, and Environment (QHSE) standards.
• Apply internal and client-specific safety and quality management systems.
• Promote a culture of continuous improvement, setting an example in achieving and exceeding company goals.

Qualifications and Education Requirements

• Graduate (BSc/BTech) in Applied Sciences, with coursework in statistics (minimum 2 years).
• Minimum 8 years of relevant industry experience.
• Relevant internship (at least 2 months) or certifications in data science/machine learning preferred.

Preferred Skills

• Strong problem-solving skills with a business-oriented mindset.
• Proficient in the following:
• R or Python for data cleaning, statistical analysis, and modeling.
• SQL, VBA, and DAX (Power BI) for querying and data manipulation.
• Understanding of data architecture principles.
• Practical knowledge of machine learning techniques (e.g., clustering, decision trees, neural networks).
• Advanced understanding of statistical methods (regression, distributions, statistical tests).
• Excellent communication skills (written and verbal) for working across teams.
• Passion for learning and adopting new technologies.

Soft Skills and Key Competencies

• Strong analytical mindset with attention to detail.
• Skilled in negotiation and influencing stakeholders.
• Flexible and adaptable with a 'never give up' attitude.
• Ability to work independently and as part of cross-functional teams.

Skills Required
Data Visualization, Statistical Analysis, Machine Learning, Sql Database, Python Programming