Data Science Associate Manager

Overview

In this role you will lead the technical delivery of customer analytics, data science and AI solutions within the Song AI & Data practice. You will navigate between hands-on development and workstream leadership, ensuring high-quality, scalable analytics and AI implementations for client outcomes. You’ll translate business problems into analytical approaches, explain technical choices to stakeholders, and drive measurable value from models and AI-enabled processes. This is a hands-on leadership role that blends coding, modelling, and project guidance to scale customer-focused AI with responsible governance.

Pay / Benefits

• competitive basic salary
• annual performance bonus
• equity opportunities
• 25 days of leave plus volunteering days
• flexible work policies
• private healthcare

Responsibilities

• Design and deliver customer analytics, data science and ML/Generative AI solutions from problem framing to production
• Make technical decisions on analytical approach, model/architecture selection, evaluation and cost/performance trade-offs
• Apply segmentation, propensity, churn, CLV and next-best-action techniques to improve customer decisions
• Write production-quality code and review others’ work across data pipelines, prompts and models
• Establish data prep, experimentation, validation and performance measurement processes
• Collaborate with engineering/product teams to move prototypes to production with MLOps practices
• Lead day-to-day technical delivery of a workstream, coaching team members and managing risks
• Communicate findings and trade-offs to technical and senior business stakeholders
• Contribute to proposals, reusable assets and best practices for customer-focused data/AI opportunities

Key requirements

• Hands-on data science and AI delivery in the customer domain
• Strong Python capability and production-quality coding
• Fundamentals of data science, experimentation and model deployment
• Generative AI knowledge including retrieval-augmented generation and prompt engineering
• Data preparation, testing, deployment, monitoring and MLOps
• Ability to translate business problems into analytical approaches and communicate results
• Understanding of Responsible AI, fairness, privacy, explainability, security and governance
• Experience leading a technical workstream and coaching others

• communication
• stakeholder management
• team coaching
• Python
• machine learning and analytics
• experimentation and evaluation

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