About us

WINT Water Intelligence is dedicated to helping businesses reduce their environmental footprint by preventing the hazards, costs, waste and environmental impact associated with water leaks and waste. Utilizing the power of artificial intelligence and IoT technology, WINT provides a solution for commercial facilities, construction sites and industrial manufacturers looking to cut water waste, reduce carbon emissions and eliminate the impact of water-leak disasters. WINT has been recognized by Fast Company and CB Insights as one of the world’s most innovative AI companies and has won multiple awards including “Next Big things in Tech” and Insurance Times’ claims prevention technology award.

Job Brief

We are seeking a Data Scientist with Robust Data Engineering Expertise who excels in both data science and engineering disciplines with a strong track record in research. This multifaceted role requires a sharp analytical mind adept at unraveling new datasets, navigating technical complexities, and exploring new domains. Critically, this position will be instrumental in enhancing our data infrastructure, pivotal for supporting sophisticated anomaly detection capabilities and managing the growing influx of IoT data.

Key Responsibilities

1. Data Engineering, Analysis, and Anomaly Detection:

• Bring 3-5 years of experience in data engineering, focusing on constructing and optimizing data pipelines and datasets.
• Conduct exploratory and quantitative data analysis, handling both large and small datasets to derive insights.
• Engage in the development and refinement of algorithms for anomaly detection, leveraging experience with IoT/Industry 4.0 data and its unique challenges.

2. Research and Data Acquisition:

• Showcase a history of independent research to unravel complex data structures and domain areas, particularly in ambiguous situations.
• Extract, integrate, and analyze IoT data streams to understand the workings of industrial devices.

3. Data Processing and Scalability:

• Clean, transform, and structure data, customizing data processing to align with client-specific needs and the nuances of IoT data streams.
• Focus on scaling data pipelines to accommodate growing data demands and complexity, ensuring robustness and efficiency in data handling.

Required Skills and Experience

• Industry Experience: At least 3-5 years in data engineering roles, with a preference for experience in IoT or industrial sectors.
• Analytical Research: A strong track record in independent research for technical problem-solving and domain-specific data understanding.
• Technical Proficiency: Advanced skills in Python programming, with Java familiarity being advantageous.
• Proficiency in data pipeline tools like Apache Kafka, Apache Beam, along with container orchestration tools such as Kubernetes for scaling applications, and cloud environments like AWS for managing large-scale data infrastructure.
• Expertise in SQL and other querying languages.
• IoT and Industry 4.0 Knowledge: Competence in understanding and researching complex IoT data streams.
• Interdisciplinary Collaboration: Proven ability to work collaboratively across diverse teams.