Forward-Deployed Data Scientist II (AI)

TL;DR

Forward-Deployed Data Scientist II (AI): Collaborating with customer analytics teams on implementations, data integration, and ML model configuration, while also extending product capabilities by improving architecture and developing reusable data pipelines and APIs. Focus on refining reinforcement learning algorithms and contributing to hirify.globalAI product strategy through customer insights.

Location: Hybrid in London, UK

Company

hirify.global is a leading customer engagement platform that empowers brands to deliver great customer experiences using composable intelligence with hirify.globalAI.

What you will do

• Collaborate with customer analytics and BI teams on implementations, including use case definition and data integration.
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components.
• Work closely with the RL pipeline development team to refine and advance reinforcement learning algorithms.
• Contribute to shaping hirify.globalAI product strategy and roadmap through customer-facing insights and technical expertise.
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success.

Requirements

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required.
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role.
• Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost).
• Skilled in SQL for querying and manipulating datasets, with experience in machine learning pipelines and model deployment.
• Ability to write well-structured, modular, documented code following strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews).
• Comfortable working directly with clients and cross-functional teams, translating technical concepts into clear business value.

Nice to have

• Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP).
• Experience with data integration/ETL and pipeline optimization.
• Experience with reinforcement learning algorithms.

Culture & Benefits

• Competitive compensation that may include equity.
• Retirement and Employee Stock Purchase Plans.
• Flexible paid time off.
• Comprehensive benefit plans covering medical, dental, vision, life, and disability, including family services like fertility benefits and equal paid parental leave.
• Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend.
• A curated in-office employee experience designed to foster community, team connections, and innovation.