Reda Bouharrou

I deliver end-to-end Data Science and Customer Experience (XM) consulting services to help organizations transform customer data into actionable business insights.

My work covers the full CX analytics lifecycle, including:

Design and configuration of advanced surveys on Qualtrics (NPS, CSAT, CES, VoC) with complex logic and embedded data,

Definition of customer experience measurement frameworks and key satisfaction metrics,

Statistical analysis of customer feedback to identify drivers of satisfaction and loyalty,

Development of dashboards and reporting for business stakeholders.

On the Data Science side, I design and deploy analytical and predictive models such as:

Supervised machine learning models (classification, regression, churn and scoring),

Unsupervised and semi-supervised learning (clustering, segmentation, anomaly detection),

Feature engineering, data cleaning and model validation,

Applied deep learning models using TensorFlow.

I work mainly with Python (Pandas, NumPy, scikit-learn, TensorFlow), SQL / Snowflake, and data visualization tools, with a strong focus on business value, interpretability and decision-making support.

Reda Data Consulting supports clients across insurance, healthcare, services and e-commerce, combining Data Science, AI and Experience Management to improve customer understanding, operational performance and strategic decision-making.

Qualtrics XM Solutions:

Build professional surveys with advanced logic, configure embedded data, automate workflows, and develop dashboards that transform feedback into actionable insights.

Data Science & Machine Learning:

Develop predictive models such as churn, segmentation, and behavioral scoring, using advanced ML techniques for improved business decision-making.

Analytics & Dashboarding:

Create clear, insightful dashboards across CRM systems and Qualtrics, tracking KPIs, customer journeys, and performance trends for better strategic decisions.

Technical Consulting & Enablement:

Support data pipelines using Python, SQL, Dataiku, and Snowflake, integrate APIs, maintain data quality, and provide training/documentation for technical teams.

Improving customer experience (CX) and configuring advanced feedback surveys. Designing and automating NPS/CSAT programs, using AI and JavaScript to personalize digital experiences and turning survey data into actionable insights via interactive dashboards.

I worked within the Data & CRM Analytics team, focusing on the analysis and exploitation of large-scale customer and commercial data to support business performance and decision-making.

My main responsibilities included:

Designing and maintaining CRM analytics dashboards to monitor sales activity, customer behavior, leads performance and operational KPIs,

Performing statistical analyses to detect anomalies, trends and performance gaps across business processes,

Managing and transforming data flows using Snowflake and SQL, ensuring data quality and consistency,

Building data pipelines in Dataiku for data preparation, feature engineering and analytics workflows,

Developing a machine learning lead scoring model to predict conversion probability of web leads, using supervised learning techniques,

Collaborating with business teams (marketing, sales, operations) to translate business needs into analytical solutions and actionable insights.

This role allowed me to strengthen my expertise in business analytics, data engineering and applied machine learning, in a real production environment with strong business impact.