Data Scientist/Engineer- PERM (West)
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Summary
A junior Data Scientist/Engineer (0-2 years) in Singapore who collects, cleans, and analyzes large datasets, builds data pipelines, and brings machine learning models into production. Core stack includes Python (pandas, scikit-learn), big data tools (Hadoop, Spark), cloud platforms (AWS/GCP/Azure), and API frameworks like Flask or FastAPI.
We are looking for a
Data Scientist/Engineer
who is a versatile professional who uses analytical, statistical, and programming skills to collect, analyze, and interpret large datasets to help organizations make data-driven decisions. Job Responsibilities: Work closely with a team of scientists and researchers to concept and iterate on software development Develop and deploy data science prototypes, with a focus on bringing machine learning models into production. Working with Big Data Tools: Use technologies like Hadoop, Spark, and distributed databases to handle large-scale datasets. Work with cloud-based data platforms like AWS, Google Cloud, or Azure for storage, computing, and analysis. Design and implement scalable and high-performance machine learning models, with a focus on troubleshooting performance and accuracy issues Gather structured and unstructured data from various sources such as databases, web services, APIs, and data streams. Build data cleaning and augmentation pipelines for both machine learning and deep learning model-based projects Automate processes and workflows for efficient delivery of data science products via scripting and open source tools. Job Requirements:
Degree in Computer Science, Computer Engineering or equivalent 0-2 years of relevant experience Experience in real-world data science projects, internships, hackathons, and personal projects Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn,matplotlib, and seaborn Knowledgeable in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI Familiar with databases (e.g. NoSQL, PostgreSQL, MongoDB) and SQL for data storage and retrieval Originally posted on Himalayas
Data Scientist/Engineer
who is a versatile professional who uses analytical, statistical, and programming skills to collect, analyze, and interpret large datasets to help organizations make data-driven decisions. Job Responsibilities: Work closely with a team of scientists and researchers to concept and iterate on software development Develop and deploy data science prototypes, with a focus on bringing machine learning models into production. Working with Big Data Tools: Use technologies like Hadoop, Spark, and distributed databases to handle large-scale datasets. Work with cloud-based data platforms like AWS, Google Cloud, or Azure for storage, computing, and analysis. Design and implement scalable and high-performance machine learning models, with a focus on troubleshooting performance and accuracy issues Gather structured and unstructured data from various sources such as databases, web services, APIs, and data streams. Build data cleaning and augmentation pipelines for both machine learning and deep learning model-based projects Automate processes and workflows for efficient delivery of data science products via scripting and open source tools. Job Requirements:
Degree in Computer Science, Computer Engineering or equivalent 0-2 years of relevant experience Experience in real-world data science projects, internships, hackathons, and personal projects Expertise in Python programming and using libraries for data processing, visualization, and model development, including pandas, numpy, scikit-learn,matplotlib, and seaborn Knowledgeable in API concepts and libraries, and experienced in utilizing them for testing and deployment, leveraging frameworks such as Flask, Django, or FastAPI Familiar with databases (e.g. NoSQL, PostgreSQL, MongoDB) and SQL for data storage and retrieval Originally posted on Himalayas
