Senior Manager - Data Analytics

Key Responsibilities:

• Collaborate with stakeholders to identify, scope, and execute data-driven business solutions.
• Extract, clean, and analyze large datasets from internal databases.
• Develop custom data models, machine learning algorithms, and predictive models to address key business challenges.
• Operationalize models into structured software programs or business processes.
• Monitor model performance and ensure continuous improvement and data integrity.
• Assess and improve the accuracy of data sources and data collection methods.
• Implement recommendations derived from data analysis into business operations.
• Communicate results and insights effectively with both technical and non-technical stakeholders.
• Provide post-implementation support to track KPIs and ensure outcomes are achieved.

Key Performance Indicators (KPIs):

• Operational and Financial Impact: Measured improvements in time or cost savings following model or tool implementation.
• Stakeholder Satisfaction: Feedback scores and qualitative input from end users regarding usability and value of delivered solutions.

Qualifications and Education Requirements:

• Bachelor's degree (BSc/BTech) in Applied Sciences, Mathematics, Statistics, Computer Science, or a related field.
• Completion of Year 2 Statistics coursework is required.
• Internship experience (min. 2 months) OR recognized certifications in data science, analytics, or related fields.

Preferred Technical Skills:

• Programming: Proficiency in Python or R (data cleaning, modeling, statistical analysis).
• Data Handling: Strong skills in SQL, Power BI (DAX), and VBA.
• Machine Learning: Familiarity with techniques such as clustering, decision trees, neural networks, etc.
• Statistical Concepts: Regression, distributions, statistical tests, and real-world application.
• Data Architecture: Experience working with structured data models and data pipelines.

Soft Skills and Competencies:

• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills.
• Ability to collaborate across teams and present data insights to stakeholders.
• High attention to detail and ability to manage multiple projects simultaneously.
• Negotiation and persuasion abilities when influencing data-driven decisions.
• Positive attitude with a never give up mindset.
• Adaptability and flexibility in dynamic environments.