Data Scientist II
Remote, Glasgow, UK| Full-Time
Zonda is redefining the future of housing. We are perfectly placed in the heart of the fast-growing real estate industry. We are making big bets on the future of real-estate, trailblazing a 2030 vision for the industry. Here at Zonda, you’ll be able to use your passion and curiosity to drive the next generation of real estate analysts, advisors, technologists, and marketers.
Zonda is looking for a passionate Data Scientist II to help create, evolve and expand our team. Zonda looks for people who can grow, think, dream, and create. When you join our team, you’ll be in a unique position to make a change with every project. You’ll use your full range of skills to build great relationships and experiences and learn about the real estate industry, economics, marketing and data. You’ll be supported with the necessary tools, and you'll be working with an awesome and like-minded team. Our teams are innovative, diverse, multidisciplinary, and collaborative - all working to build the future of housing.
The Data Scientist II is a mid-level position responsible for Data Science and modelling in the realm of housing data. The Data Scientist would achieve this through the application of established processes of data analytics, experiments, engaging with stakeholders with the findings and subsequently developing code for production. This will involve working with other data scientists or ML Engineers and business stakeholders. This role requires good cross disciplinary skills across databases, analytics, statistics, and modelling. The person should be able to work independently in a DevOps environment, often collaborating with stakeholders from other technical teams as well as business teams. Good communication skills with an ability to demystify ML algorithms and capabilities is a must, as stakeholders in ML products include software engineering teams as well as non-technical business partners.
Responsibilities:
Collection, cleaning, and pre-processing of data for solving business problems. Conduct exploratory data analysis to identify trends, patterns, and correlations in the data. Develop statistical and machine learning models for data quality improvements, predictions, segmentation, and imputation. Engage business stakeholders from analysis using visualisations and findings. Collaborate with stakeholders to define requirements and deliverables. Ownership of documentation related to datasets, model selection, training experiments, and production infrastructure. Monitor ML models in production, setting metrics to identify drift, and establish corrective measures for restoring model performance. Identify and implement appropriate tools for monitoring product performance in inference. Continual learning and self-improvement with a focus on latest trends, techniques, and best practices in Data Science and Machine Learning.
Requirements:
Bachelor's degree in computer science, Statistics, Mathematics, or a related field. 3+ years of experience in Data Science, Data Analytics, Machine learning, or a related field. Proficient in Python and working knowledge of libraries NumPy, Pandas, Matplotlib, and scikit-learn etc. Proficient in SQL for data extraction, transformation and analysis. Strong mathematical, analytical, and problem-solving skills. Strong understanding of statistical modelling, hypothesis testing and sampling methods. Understanding of dataset preparation, splits, data quality control, and management. Knowledge of data pre-processing and feature engineering techniques. Sound understanding of software development best practices and DevOps. Experience with version control systems like Git. Experience with cloud computing platforms like AWS, Google Cloud, or Azure. Knowledge and implementation of advanced data visualisation techniques. Excellent communication and teamwork skills.
Nice to have
Masters in a specific field such as Statistics, Data Science, Machine Learning, or AI. Familiarity with containerization and orchestration tools like Docker, Airflow, Kubernetes etc. Familiarity with data pipelines and associated tools like dbt. Experience with cloud-based data science tools such as AWS Sagemaker. Basic understanding of housing market, housing economics, mortgages, and housing construction. Familiarity with building and maintaining APIs with standard tools such as FastAPI or Flask.
Why People Love Working Here
We offer meaningful work and opportunities for career growth Interesting product roadmap with room for innovation Competitive Salary Employee Assistance Program (EAP) Live Meditation Sessions Employee Recognition Platform Virtual Wellness Program Visionary Leadership Team
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