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Big Data & Special CVM Projects Specialist
DSM, Dar es Salam, TZ
Actively hiring, first seen by us today- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
About Vodafone Group
We are a leading international Telco, serving millions of customers.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 4, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Vodafone Group is hiring
45 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- Databricks
- Spark
Where the posting names them
Join Us Role purpose: The Big Data & Special CVM Projects Specialist is responsible for leveraging advanced analytics, machine learning, and customer intelligence to drive sustainable customer and revenue growth across the M Pesa business. The role develops and operationalizes data-driven CVM strategies that improve customer acquisition, engagement, retention, product penetration, and customer lifetime value. The role is accountable for: • Co-creating and deploying advanced machine learning and artificial intelligence solutions that drive revenue growth, cost optimization, customer retention, and enhanced customer experience. • Developing big data monetization propositions and managing their end-to-end execution to unlock commercial value from customer data and behavioral insights. • Delivering actionable customer insights, predictive analytics, and segmentation strategies that support M-Pesa objectives, commercial targets, and business decision-making. • Designing and optimizing personalized customer lifecycle campaigns, including acquisition, activation, retention, reactivation, cross-sell, and upsell initiatives. • Driving customer value enhancement through time to action, causal inference, difference in difference propensity modelling, churn prediction and customer journey optimization initiatives. • Measuring and improving campaign effectiveness through Causal Inferences, advanced analytics, experimentation, and continuous optimization of customer engagement strategies. • Promoting effective data governance, data quality, and responsible use of customer information while ensuring compliance with regulatory and privacy requirements. Key accountabilities and decision ownership: • Causal Inference, Transformer Based Modelling, Classical ML Modelling its Lifecycle. • ETL, Feature Engineering Alternatives & Embedding Infrastructure - AI Product Lifecycle Strategy • Explainable AI (XAI) & Model Governance • E2E go to market execution for big data and special projects propositions. • Identify Analyze and Interpret trends or patterns in complex data sets. Core competencies, knowledge and experience: • Excellent analytical, logical and casual reasoning skills. • Strong stakeholder management skills • Ability to anticipate customer, competitor and market dynamics • Able to challenge the status quo Must have technical/professional qualifications: • Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Actuarial Science, Artificial Intelligence, or a related quantitative discipline. • Master's Degree in Data Science, Analytics, Artificial Intelligence, Business Analytics, or MBA (preferred). • Minimum 5–7 years' experience in Big Data Analytics, Data Science, Customer Analytics, CVM, Machine Learning, or Commercial Analytics. • Advanced proficiency in SQL and data querying tools. • Experience using Python, Spark, Databricks, or equivalent analytics tools. • Experience working with Big Data platforms, cloud analytics environments, and machine learning frameworks. • Strong understanding of Fintech ecosystems. • Experience developing and deploying predictive models in a production environment. Who we are
Your next step
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About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
Join Us
Role purpose:
The Big Data & Special CVM Projects Specialist is responsible for leveraging advanced analytics, machine learning, and customer intelligence to drive sustainable customer and revenue growth across the M Pesa business. The role develops and operationalizes data-driven CVM strategies that improve customer acquisition, engagement, retention, product penetration, and customer lifetime value.
The role is accountable for:
• Co-creating and deploying advanced machine learning and artificial intelligence solutions that drive revenue growth, cost optimization, customer retention, and enhanced customer experience.
• Developing big data monetization propositions and managing their end-to-end execution to unlock commercial value from customer data and behavioral insights.
• Delivering actionable customer insights, predictive analytics, and segmentation strategies that support M-Pesa objectives, commercial targets, and business decision-making.
• Designing and optimizing personalized customer lifecycle campaigns, including acquisition, activation, retention, reactivation, cross-sell, and upsell initiatives.
• Driving customer value enhancement through time to action, causal inference, difference in difference propensity modelling, churn prediction and customer journey optimization initiatives.
• Measuring and improving campaign effectiveness through Causal Inferences, advanced analytics, experimentation, and continuous optimization of customer engagement strategies.
• Promoting effective data governance, data quality, and responsible use of customer information while ensuring compliance with regulatory and privacy requirements.
Key accountabilities and decision ownership:
• Causal Inference, Transformer Based Modelling, Classical ML Modelling its Lifecycle.
• ETL, Feature Engineering Alternatives & Embedding Infrastructure - AI Product Lifecycle Strategy
• Explainable AI (XAI) & Model Governance
• E2E go to market execution for big data and special projects propositions.
• Identify Analyze and Interpret trends or patterns in complex data sets.
Core competencies, knowledge and experience:
• Excellent analytical, logical and casual reasoning skills.
• Strong stakeholder management skills
• Ability to anticipate customer, competitor and market dynamics
• Able to challenge the status quo
Must have technical/professional qualifications:
• Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Actuarial Science, Artificial Intelligence, or a related quantitative discipline.
• Master's Degree in Data Science, Analytics, Artificial Intelligence, Business Analytics, or MBA (preferred).
• Minimum 5–7 years' experience in Big Data Analytics, Data Science, Customer Analytics, CVM, Machine Learning, or Commercial Analytics.
• Advanced proficiency in SQL and data querying tools.
• Experience using Python, Spark, Databricks, or equivalent analytics tools.
• Experience working with Big Data platforms, cloud analytics environments, and machine learning frameworks.
• Strong understanding of Fintech ecosystems.
• Experience developing and deploying predictive models in a production environment.
Who we are
We are a leading international Telco, serving millions of customers. At Vodafone, we believe that connectivity is a force for good. If we use it for the things that really matter, it can improve people's lives and the world around us. Through our technology we empower people, connecting everyone regardless of who they are or where they live and we protect the planet, whilst helping our customers do the same.
Belonging at Vodafone isn't a concept; it's lived, breathed, and cultivated through everything we do. You'll be part of a global and diverse community, with many different minds, abilities, backgrounds and cultures. ;We're committed to increase diversity, ensure equal representation, and make Vodafone a place everyone feels safe, valued and included.
If you require any reasonable adjustments or have an accessibility request as part of your recruitment journey, for example, extended time or breaks in between online assessments, please refer to https://careers.vodafone.com/application-adjustments/ for guidance.
Together we can.
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- Location & working pattern
DSM, Dar es Salam, TZ
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