About the role

The Data Scientist will be responsible for analyzing complex datasets to derive actionable insights. They will develop and implement predictive models to support business decision-making processes.

What they look for

Data Science

Requirements

Candidates should possess strong analytical skills and experience in data modeling. Proficiency in relevant data science tools and methodologies is required for this role.

Full description

Leverage advanced analytics, machine learning, and AI techniques to solve complex business problems, generate actionable insights, and build predictive solutions that drive business growth.

Work closely with product, data and marketing teams to develop data science solutions, optimize customer experiences, and unlock business value through data-driven innovation.

Translate complex business problems into scalable machine learning, AI and advanced analytics solutions that deliver measurable business value.

Design and develop customer intelligence solutions to improve customer acquisition, engagement, retention, personalization, and lifetime value.

Build, validate, deploy, and monitor predictive models and recommendation systems across key business use cases.

Evaluate emerging AI, Generative AI, and machine learning technologies, identifying opportunities to accelerate innovation and improve business outcomes.

Drive continuous improvement through automation, optimization and standardization of analytics and data science workflows.

Design and support experimentation frameworks, including A/B testing, uplift modeling, and causal impact analysis, to enable data-driven decision-making.

Partner with Data engineering and product teams to productionize, deploy and scale machine learning and AI solutions in production environments.

Analyze large, complex datasets to uncover actionable insights and communicate recommendations to business stakeholders.

Present technical concepts, analytical findings, and strategic recommendations effectively to both technical and non-technical audiences.

Contribute to business excellence initiatives by identifying opportunities to improve operational efficiency and customer experience through data and AI.

Requirements

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field.

5–8 years of experience in Data Science, Machine Learning, Advanced Analytics, or AI-driven product development.

Strong proficiency in Python and SQL, with a solid understanding of machine learning algorithms and analytical techniques.

Proven experience building, validating, and deploying predictive and prescriptive models to solve business problems.

Hands-on experience with Azure Databricks, cloud-based analytics platforms, and large-scale data environments.

Strong knowledge of statistical modeling, experimentation (A/B testing), forecasting, clustering, classification, recommendation systems, and model evaluation.

Experience with Generative AI, Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, or AI-powered automation solutions is highly desirable.

Experience translating business problems into scalable data science solutions and collaborating with cross-functional teams to deliver measurable business impact.

Background in Retail, Customer Analytics, Digital Analytics, E-commerce, Loyalty, or CRM analytics is preferred.

Excellent communication, stakeholder management, and data storytelling skills, with the ability to explain complex analytical concepts to both technical and non-technical audiences.

Strong problem-solving skills with the ability to balance technical excellence, business impact, and strategic thinking.