Technology
Remote
Riyadh, KSA
We are seeking a Data Scientist who will lead analytical design, model development, and experimental on across high-impact customer analytics initiatives such as Customer Lifetime Value (CLV), Predictive NPS/CSAT, Churn/Retention, and Customer Segmentation. The ideal candidate has strong hands-on expertise in predictive modelling, large-scale distributed computing (PySpark), and real-world deployment experience. A proven ability to work with large, complex datasets to translate business needs into scalable analytical solutions.
About the job
We are seeking a Data Scientist who will lead analytical design, model development, and experimental on across high-impact customer analytics initiatives such as Customer Lifetime Value (CLV), Predictive NPS/CSAT, Churn/Retention, and Customer Segmentation. The ideal candidate has strong hands-on expertise in predictive modelling, large-scale distributed computing (PySpark), and real-world deployment experience. A proven ability to work with large, complex datasets to translate business needs into scalable analytical solutions.
Key Responsibilities
What we expect from you
Customer Analytics & Predictive Modelling
- Build and maintain CLV models (historical and/or predictive) incorporating revenue, costs, engagement signals, and churn/retention.
- Develop predictive NPS, satisfaction, and churn models to identify high-risk customers and key drivers of experience.
- Design customer segmentation (value-based, behavioral, RFM, clustering, predictive) to support targeting, campaigns, and product design.
- Ensure all models are robust, monitored, and explainable, with clear links to business objectives and measurable impact.
Data Wrangling & Feature Engineering
- Work with large, complex datasets from multiple sources such as CRM, transactional and interaction data, digital journeys, contact center data, and surveys/VoC.
- Use PySpark, Python, and SQL to clean, transform, and join data; build scalable feature pipelines.
- Partner with engineering to productionize models via batch jobs, APIs, and dashboards; ensure reliability and performance.
Evaluation & Explainability
- Define and track relevant metrics (AUC, F1, uplift, calibration, segment performance, stability, etc.).
- Use explainability techniques (feature importance, SHAP, or similar) to communicate model behavior clearly.
- Contribute to documentation, model monitoring, and retraining plans to sustain performance over time.
Stakeholder Engagement & Storytelling
- Translate business questions into clear analytical problems, hypotheses, and success criteria.
- Present insights and recommendations to CX, Marketing, Product, Digital, and Operations stakeholders.
- Prepare concise decks, summaries, and dashboards to support decisions and drive adoption.
Qualification
Experience
- 4+ years of hands-on experience in Data Science and Predictive Modelling within established or high-growth organizations.
- Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
- Proven experience in end-to-end delivery of data science solutions—from problem framing and data preparation to model deployment and monitoring.
- Demonstrated delivery of at least one (production or advanced PoC) of the following:
- CLV / Profitability
- Churn / Propensity
- Predictive NPS / CSAT
- Customer segmentation at scale
Technical Skills (Must-Have)
- Strong proficiency in Python (pandas, scikit-learn, MLlib, or similar libraries).
- Strong proficiency in PySpark and working with large datasets on distributed platforms.
- Advanced SQL skills for complex querying, data transformation, and performance optimization.
- Experience using Power BI, Tableau, or similar tools for analytics, dashboards, and data storytelling.
- Experience with MLflow (or similar) for experiment tracking, model versioning, and lifecycle management.
- Solid understanding and hands-on experience with core Data Science concepts, including:
- Supervised learning: classification, regression, uplift modelling
- Unsupervised learning: clustering, dimensionality reduction
- Feature engineering, model tuning, and validation
- Experience working in a cloud or big data environment (Azure, AWS, GCP, Databricks, or similar).
Preferred Qualifications (Bonus)
- Experience with Experience Management platforms such as Medallia, Qualtrics, or similar.
- Strong practical MLOps habits (monitoring, drift checks, reproducible pipelines, CI/CD collaboration).
- Exposure to NLP and text analytics (e.g., survey verbatims, call-center transcripts, complaint logs) applied to customer experience or insight use cases.
What you can expect from us
At New Metrics, we are committed to creating an inclusive, flexible, human-centric and supportive work environment.
When you join our team, you can expect:
- Exceptional trust based culture that fosters inclusion, creativity, and innovation:
- 91% of employees feel engaged, reflecting our ongoing efforts to deliver the best in class employee experience
- 94% of our employees feel included and have a sense of belonging
- 94% of employees trust their manager
- Collaboration with a passionate and high-performing team that values appreciation of individual attributes and diverse perspectives
- Exposure to a global brand known for its commitment to excellence and making a difference in creating human value
- A comprehensive focus on flexibility, wellness and result orientation in operation
- Strong focus on life-long learning and continuous development, along with opportunities to enhance your skills and knowledge
- Equal opportunities for growth and development, supported by subsidized professional qualifications and paid professional memberships to advance your career
- A commitment to environmental sustainability, creating a positive impact on the world around us
Join our passionate team at New Metrics and make a meaningful impact on the world of experience management! Our values, mission, and culture drive us to create flawless experiences that matter. If you’re ready to delve deeper and contribute to our vision, apply now. We can’t wait to hear from you!
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