Senior Data Scientist

Position Summary:

We are seeking an accomplished Senior Data Scientist with deep expertise in Generative AI, and solid foundations in ML Engineering to join our forward-thinking AI & Data Science team. You will play a pivotal role in leading cutting-edge AI initiatives, scaling data-driven strategies, and shaping the future of AI at Property Finder.

This senior role requires strong technical and research depth, a collaborative mindset, and a proven ability to translate business challenges into impactful AI solutions. You will also act as a mentor to junior scientists and influence strategic decision-making across the company.

 

Key Responsibilities:

• Lead the design and implementation of complex predictive and optimization models using classical ML/statistical methods, deep learning architectures, and generative techniques.

• Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such as enhanced personalization, lead qualification, content generation, and workflow automation.

• Own the end-to-end ML lifecycle: from hypothesis generation, experimentation, evaluation, and explainability, to scalable deployment in production systems.

• Develop and enforce rigorous evaluation and monitoring pipelines, including A/B testing, drift detection, and model fairness/robustness.

• Guide the development of advanced analytics and visualization solutions to support strategic business decisions at scale.

• Collaborate closely with engineering teams to ensure resilient, low-latency, and production-grade deployment of AI systems.

• Embed trust, transparency, and auditability in all models—ensuring alignment with ethical AI and governance frameworks.

• Stay abreast of the latest in AI research and industry trends to keep our technology stack at the forefront.

• Implement MLOps and deployment best practices (CI/CD, automated workflows, model registry, versioning, and lifecycle management).

Cross-Team Collaboration:

• Act as a technical leader and mentor for junior team members, fostering a culture of excellence, innovation, and continuous learning.

• Collaborate with Data Platform and Engineering teams to optimize model deployment pipelines and infrastructure.

• Partner with Product, Strategy, Commercial, and Executive stakeholders to define AI roadmaps, align on business priorities, and communicate insights effectively.

 

Desired Qualifications:

• Education: Master’s or PhD in Computer Science, Machine Learning, Data Science, or a related field.
• Experience: 

  • 5+ years of experience in applied data science or machine learning engineering roles.

  • Proven track record of deploying models in production environments with measurable business impact.

  • Experience guiding junior data scientists or leading end-to-end ML projects independently.

• Technical Skills:

  • Expertise in supervised/unsupervised learning, deep learning (CNNs, RNNs, transformers), and statistical modeling.

  • Strong foundation in scenario modeling, optimization, and evaluation metrics for performance and fairness.

  • Proficiency in Python (pandas, NumPy, scikit-learn) and deep learning libraries (PyTorch or TensorFlow).

  • Hands-on experience with LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) pipelines.

  • Experience integrating ML models via APIs and embedding AI in enterprise systems.

  • Deep knowledge of cloud platforms (AWS/GCP/Azure) and containerized deployments (Docker, Kubernetes).

  • Familiarity with ML pipelines, model registries, CI/CD, Git-based version control, and production monitoring.

• Soft Skills:
  

  • Exceptional communication and stakeholder management skills across technical and non-technical audiences.

  • Strategic thinking with the ability to connect AI/ML capabilities to core business goals.

  • Demonstrated ability to thrive in a fast-paced, collaborative, and dynamic environment.Strategic mindset with the ability to translate business goals into data-driven initiatives.