Data Scientist (EGG Digital Contract 18 Months)

About the Role

Data Scientist at Ascend Group. EGG Digital Contract (18 Months). Onsite.

Responsibilities

• Collaborate with business, product, and engineering teams to identify opportunities for data-driven decision making and advanced analytics solutions
• Design, develop, and deploy statistical, machine learning, and optimization models, including credit and income modeling
• Build scalable data pipelines and workflows using big data technologies (e.g., Databricks, PySpark) and cloud platforms
• Develop and maintain production-grade solutions, including APIs and backend services, following sound software engineering practices
• Analyze large, complex datasets to uncover customer behavior patterns, insights, and drivers of customer experience
• Monitor model performance, data quality, and system reliability; retrain and optimize models as business conditions evolve
• Communicate analytical findings, assumptions, and recommendations clearly to technical and non-technical stakeholders

Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field
• 2-3 years of hands-on experience as a Data Scientist delivering end-to-end analytics or machine learning solutions
• Strong experience in descriptive, predictive, and prescriptive analytics, including machine learning, forecasting, and optimization
• Proficiency in Python and experience with big data frameworks such as PySpark and Databricks
• Hands-on experience with ETL processes, workflow orchestration, databases, and query performance optimization
• Strong software development skills, including API development, backend systems, version control (Git), and basic software architecture
• Experience with Cloud technology and databases (Cloud AWS, Azure, GDP)
• Optional: Exposure to Generative AI, Agentic AI, LLMs, or RAG-based solutions in production or experimentation contexts
• Strong problem-solving and communication skills

Skills

• Python; PySpark / Apache Spark; Databricks
• Cloud platforms (AWS, Azure, GDP)
• API development and backend systems; Git
• ETL processes and workflow orchestration
• Machine learning, forecasting, and optimization