Job Summary：
In this data analytic engineer role, you will play a critical support function in the company's digital development strategy. By conducting in-depth analysis of IoT, service, and test data, the role provides valuable business insights to both the company and its clients, driving continuous improvement and innovation in business operations.
Responsibilities:
1. Data Analysis: Collecting and analyzing data from various HVAC systems and devices to identify patterns, trends, and anomalies. Applying statistical methods and data visualization techniques to interpret and communicate findings.
2. Predictive Modeling: Building predictive models based on historical HVAC data to forecast equipment performance, energy consumption, maintenance needs, and optimize system efficiency. Using techniques such as regression analysis, time series analysis, and machine learning algorithms.
3. Data Cleansing and Preparation: Cleaning, transforming, and preparing HVAC data for analysis by handling missing values, outliers, and data quality issues. Collaborating with other teams to ensure data integrity, consistency, and accuracy.
4. Feature Engineering: Identifying relevant features and variables that can enhance predictive models and improve insights. This may involve working with domain experts to select meaningful indicators related to HVAC performance, weather conditions, occupancy, or other relevant factors.
5. Model Deployment: Integrating predictive models and insights into HVAC systems, platforms, or applications. Collaborating with software engineers, developers, and system integrators to ensure seamless integration and real-time decision-making capabilities.
6. Data Visualization and Reporting: Creating visually appealing and interactive dashboards or reports to communicate findings and insights derived from HVAC data. Presenting information in a clear and understandable manner to stakeholders across the organization.
7. Data-driven Decision-making: Collaborating with cross-functional teams, such as engineers, technicians, and stakeholders, to leverage data insights in optimizing HVAC system performance, energy management, maintenance planning, and overall operational efficiency.
8. Research and Innovation: Keeping up-to-date with the latest advancements in data science, machine learning, and HVAC technology. Exploring new methods, algorithms, and technologies that can enhance data analysis and drive innovation within the HVAC industry.
9. Collaboration and Stakeholder Engagement: Working closely with internal teams, customers, and partners to understand their data needs, requirements, and business objectives. Building strong relationships and providing data-driven insights to support decision-making processes.
10. Compliance and Ethics: Ensuring compliance with relevant data protection regulations and maintaining ethical practices in data handling, privacy, and security.
Qualifications:
1.Bachelor's degree or above in Mechanical Engineering with emphasis in Thermodynamics, Refrigeration, Air Conditioning, heat Transfer, or related fields, data scientists in a relevant field such as computer science, Statistics, mathematics preferred
2.Programming Languages: Proficiency in programming languages commonly used in data science like Python
3.Data Manipulation and Analysis: Skills in handling and analyzing large datasets using tools and libraries
4.Machine Learning: Understanding of machine learning algorithms and frameworks
5.Statistical Analysis: Strong foundation in statistical methods and their applications.
6.Data Visualization: Ability to create meaningful visualizations using tools
7.Big Data Technologies: Familiarity with big data tools and platforms
8.Problem-Solving: Ability to approach complex problems methodically and find effective solutions.
9.Communication: Strong skills in communicating technical information to non-technical stakeholders.
10.Critical Thinking: Ability to analyze data critically and make data-driven decisions.
11.Collaboration: Experience working in teams and collaborating with other departments.
12.Good knowledge in domains of Sales and Service Business, Customer experiences. Full spectrum understanding on the processes and data relate to Products, Sales & Customers services