Role propse
Zain Iraq is Actively recruiting to hire a Senior Data Scientist to contribute to the Customer Analytics Unit’s activities. This role involves the implementation of the advanced analytics roadmap, collaborating with various departments to prioritize business requirements, and developing as well as deploying advanced analytical models. The Senior Data Scientist will also be responsible for proactively identifying opportunities for data science initiatives, overseeing and managing data science projects, and ensuring the successful implementation and maintenance of analytical models in production
Key Accountabilities
- Collaborate with cross-functional teams to identify high-impact business problems and define data-driven solutions.
- Lead stakeholder discussions to translate business needs into analytical frameworks, clearly defining goals, assumptions, and success metrics.
- Design and lead analytical frameworks to quantify the impact of marketing initiatives (e.g., price changes, campaigns, regional launches).
- Assess product performance across lifecycle stages, including adoption, usage, retention, and revenue contribution.
- Collaborate with marketing and product teams to translate business objectives into data-driven experiments and KPIs.
- Design and implement end-to-end machine learning and statistical models to support decision-making by delivering insights and forecasts.
- Develop and maintain robust performance tracking for models in production, ensuring continuous improvement through retraining and monitoring.
- Communicate results and methodologies clearly to both technical and non-technical stakeholders.
- Build Applications and fine-tune Large language-based Models (LLMs) for enterprise use cases, ensuring models are optimised for performance and aligned with specific organisational goals.
- Stay up to date with advancements in ML and NLP; actively experiment with new techniques and tools to improve the accuracy, efficiency, and scalability of solutions.
- Identify, source, and assess the quality of relevant internal and external data; partner with data engineering and IT teams to ensure availability, integration, and governance of datasets.
- Make informed recommendations on data infrastructure and analytics tooling based on business requirements and industry’s best practices.
Educational Qualifications and Experience
- Educational Qualifications
- BSC or above in a relevant field such as Computer Science, Data Science, Mathematics, Econometrics, or related disciplines.
- Experience
- A minimum of 4 years of relevant experience, data science or ML roles.
- Technical Experience
- Machine Learning: Solid understanding of supervised & unsupervised, or reinforcement learning techniques.
- Deep Learning: Proficient in neural network architectures and frameworks such as PyTorch.
- LLMs & NLP (Preferred experience): Hands-on experience with NLP techniques and familiarity with transformer-based models.
- Causal Inference (Preferred experience): Familiarity with causal modelling techniques
- Programming: Proficiency in SQL or Python and familiarity with ML libraries.
Competencies
Behavioral Competency
- Achievement Driven
- Integrity
- Team Work
- Information Seeking
Technical Competency
- Financial Management
- Project / Program Management
- Performance Management
- Business Modelling and Analysis
- Oral and Written Communication
- Managing Information
- Technology Application
- Strategic Planning and Thinking
- IT Business Analysis
- Sales Management
IDE Competency
- Courage to Engage
- Addressing Bias
- Allyship
