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.