Data Scientist – Predictive Analytics, IoT & AI Applications

Date Posted:

2026-02-13

Country:

China

Location:

LOC3344: 7-8/F, Building N1, Fusion New Bund, No. 8, Lane 131, New Bund Avenue, Pudong, Shanghai, China

Job Title: Data Scientist – Predictive Analytics, IoT & AI Applications

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Job Description

We are seeking a motivated and hands-on Data Scientist to join our Data Science & Analytics team. This role focuses on building predictive models for industrial IoT applications, delivering data analysis and reporting solutions, and supporting generative AI initiatives. The ideal candidate will have 3+ years of experience with solid technical skills in machine learning, data analytics, and familiarity with LLM/GenAI technologies.

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Responsibilities

Data Analysis & Reporting

· Perform exploratory data analysis (EDA) on structured and unstructured datasets to uncover business insights

· Design and build data dashboards and visualization solutions tailored to operational and business requirements

· Conduct data quality verification, data cleaning, and feature engineering to support downstream modeling tasks

· Write and optimize SQL queries for data extraction, transformation, and performance tuning

Predictive Modeling & Machine Learning

· Build and deploy predictive models for industrial scenarios such as predictive maintenance, quality prediction, and yield optimization

· Execute end-to-end ML workflows including feature engineering, model training, evaluation, and iteration

· Develop rule engines and hybrid systems combining ML models with business logic

· Analyze time-series data from IoT sensors (e.g., equipment telemetry, production logs) for anomaly detection and pattern recognition

Industrial IoT Analytics

· Participate in industrial IoT projects, supporting data solutions from sensor data ingestion to actionable insights

· Collaborate with domain experts to translate business problems into analytical frameworks

· Support data pipeline development and maintenance on cloud platforms

GenAI / LLM Support

· Assist in building and maintaining LLM-based applications such as document Q&A and text classification

· Support prompt engineering and RAG (Retrieval-Augmented Generation) pipeline development

· Evaluate and test GenAI tools and APIs for potential business use cases

Collaboration & Documentation

· Work closely with senior data scientists, engineers, and business stakeholders to deliver projects on time

· Document analysis processes, model designs, and results in English

· Maintain code quality and version control using Git

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Experience / Qualifications

Required

· Master's degree in Computer Science, Data Science, Statistics, Software Engineering, or related field

· Minimum 3 years of experience in data science, data analytics, or machine learning roles

· Proficient in Python with hands-on experience in libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib/Seaborn

· Strong SQL skills with experience in data extraction, transformation, and query optimization

· Solid understanding of machine learning fundamentals: regression, classification, clustering, ensemble methods, and model evaluation

· Experience with time-series analysis and statistical modeling

· Hands-on experience with data visualization tools (e.g., Power BI, Tableau, or Python-based dashboards)

· Familiarity with cloud platforms, preferably Azure (Databricks, Data Factory) or AWS equivalent

· Basic understanding of GenAI/LLM concepts including prompt engineering, RAG architecture, and API usage (e.g., OpenAI API, LangChain)

· Familiar with Git for version control

· Good English reading and writing skills for technical documentation

Nice to Have

· Experience in industrial/manufacturing IoT projects (e.g., predictive maintenance, quality analytics, OEE optimization)

· Experience with PySpark or Spark MLlib for large-scale data processing

· Hands-on experience with Databricks for ML experiments or data engineering

· Familiarity with Python testing frameworks (Pytest, UnitTest)

· Experience with LLM fine-tuning or deploying LLM-based applications

· Domain knowledge in semiconductor, manufacturing, energy, or industrial automation

· Exposure to MLOps practices (model monitoring, CI/CD for ML)

If you live in a city, chances are we will give you a lift or play a role in keeping you moving every day. 

Otis is the world’s leading elevator and escalator manufacturing, installation, and service company. We move 2.4 billion people every day and maintain approximately 2.4 million customer units worldwide, the industry's largest Service portfolio.  

You may recognize our products in some of the world’s most famous landmarks including the Eiffel Tower, Empire State Building, Burj Khalifa and the Petronas Twin Towers! We are 72,000 people strong, including engineers, digital technology experts, sales, and functional specialists, as well as factory and field technicians, all committed to meeting the diverse needs of our customers and passengers in more than 200 countries and territories worldwide. We are proud to be a diverse, global team with a proven legacy of innovation that continues to be the bedrock of a fast-moving, high-performance company.  

When you join Otis, you become part of an innovative global industry leader with a resilient business model. You’ll belong to a diverse, trusted, and caring community where your contributions, and the skills and capabilities you’ll gain working alongside the best and brightest, keep us connected and on the cutting edge.  

We provide opportunities, training, and resources, that build leadership and capabilities in Sales, Field, Engineering and Major Projects and our Employee Scholar Program is a notable point of pride, through which Otis sponsors colleagues to pursue degrees or certification programs.   

Today, our focus more than ever is on people. As a global, people-powered company, we put people – passengers, customers, and colleagues – at the center of everything we do.  We are guided by our values that we call our Three Absolutes – prioritizing Safety, Ethics, Quality in all that we do. If you would like to learn more about environmental, social and governance (ESG) at Otis click here.  

Become a part of the Otis team and help us #Buildwhatsnext! 

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