We are looking for a **Data 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.
• *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
