Data Scientist

Roles and responsibilities

We are looking for a highly experienced Data Scientist (Level III) with foundational skills in Machine Learning Engineering and MLOps to join our innovative AI & Data Science team. The ideal candidate will bring expertise in advanced predictive modeling, architecting scalable data solutions, and integrating AI systems into enterprise platforms. A strong research background (preferably a PhD) combined with a practical understanding of MLOps principles is essential to excel in this role.

This position plays a critical role in shaping the future of AI-driven decision-making at Property Finder, driving data strategy, and delivering impactful AI solutions.

Key Responsibilities

Data Science (Level III):

• Expertise in designing and implementing complex data models and predictive analytics.
• Mastery in programming with Python or R, including scripting for automation.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop).
• Advanced knowledge of deep learning and model optimization techniques.
• Expertise in AI optimization and reinforcement learning.
• Design and implement advanced predictive models and AI solutions tailored to strategic business needs.
• Architect scalable, data-driven solutions for high-impact decision-making.
• Develop and deploy advanced analytics and visualization tools to support business insights.
  

MLE/MLOps (Level I or II):

• Collaborate with MLE/MLOps engineers to ensure models are optimized for deployment in production environments.
• Understand and support the deployment of AI/ML models using basic MLOps tools and pipelines.
• Work with CI/CD processes for automating model workflows and managing version control.
• Gain foundational experience in model monitoring and lifecycle management.
  

Cross-Team Collaboration:

• Partner with the MLE/MLOps team to optimize model deployment and operational workflows.
• Work closely with the Strategy, BI, Engineering, and Product teams to align on project objectives and ensure smooth deployment of solutions.

Desired candidate profile

• Education: Master’s or PhD in Computer Science, Data Science, Machine Learning, or a related field (PhD preferred).
• Experience: At least 3+ years in data science roles with demonstrated leadership experience and foundational exposure to MLE/MLOps practices.
• Technical Skills:
  • Working knowledge of advanced predictive modeling, scenario analysis, and statistical methodologies.
  • Proficiency in Python or R and libraries like TensorFlow, PyTorch, Scikit-learn.
  • Integration of AI systems into enterprise platforms and workflows.
  • Experience with API development and connecting AI systems to external platforms.
  • Good experience in architecting scalable data solutions and integrating AI systems.
  • Advanced analytics and visualization skills with tools like Tableau or Power BI.
  • Working kowledge in deep learning techniques, including CNNs, RNNs, transformers, and reinforcement learning.
  • Experience in designing, fine-tuning, and deploying Large Language Models (e.g., GPT, BERT, T5).
  • Developing applications using generative models for personalized recommendations, content creation, or automation.
  • Proficiency in transfer learning and prompt engineering for LLMs.
  • Proficient in leveraging cloud platforms (AWS, GCP, Azure) for scalable AI solutions.
  • Foundational understanding of ML pipelines and deployment processes.
  • Experience with version control systems (e.g., Git) and basic CI/CD workflows.
  • Familiarity with containerization tools like Docker.
  • Good working knowledge of cloud platforms like AWS, GCP, or Azure.
• Soft Skills:
  • Effective communication and collaboration skills, particularly in cross-functional environments.
  • Strategic mindset with the ability to translate business goals into data-driven initiatives.