Data Scientist
1 day ago
Unlock Your Potential as a Machine Learning Engineer
We are seeking a highly skilled Machine Learning Engineer to join our innovative team. As a key member, you will design, develop, and deploy robust, scalable solutions for real-world financial challenges.
Key Responsibilities- Develop and optimize machine learning models using Python libraries such as TensorFlow, PyTorch, or scikit-learn to solve complex financial problems.
- Builtdynamic graph-based algorithms and data structures using libraries like NetworkX or PyG (PyTorch Geometric) for applications such as network analysis, fraud detection, or knowledge graphs.
- Write complex SQL queries to manage, transform, and analyze large datasets, ensuring efficient data pipelines and integration with databases like PostgreSQL, MySQL, or SQLite.
- Design and implement generative AI models (e.g., LLMs, GANs, or VAEs) using frameworks like Hugging Face, LangChain, or custom solutions for tasks such as text generation, data augmentation, or synthetic data creation.
- Write clean, modular, and maintainable Python code, adhering to best practices, and optimize for performance and scalability in production environments.
- Work closely with data scientists, engineers, and business teams to translate requirements into technical solutions, contributing to architectural decisions and innovative AI strategies.
- Builddata pipelines to preprocess and integrate data for machine learning and graph-based applications, using tools like Apache Airflow or Pandas.
- Deploy machine learning and generative AI models to production environments using tools like Docker, Kubernetes, or cloud platforms (AWS, GCP, Azure).
Requirements:
- Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or a related field.
- Professional Experience:
- 5+ years of professional Python programming experience.
- 3+ years of hands-on experience in machine learning model development and deployment.
- Proven expertise in graph algorithms, graph databases (e.g., Neo4j), or graph-based machine learning.
- Strong proficiency in SQL and relational database management.
- 2+ years working with generative AI models (e.g., LLMs, GANs, or diffusion models).
- Expert-level Python programming (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch).
- Experience with graph libraries (e.g., NetworkX, PyG, or DGL) and graph databases.
- Advanced SQL skills for querying and optimizing large datasets.
- Familiarity with generative AI frameworks (e.g., Hugging Face, LangChain, or OpenAI APIs).
- Proficiency in version control (Git), CI/CD pipelines, and containerization (Docker).
- Experience with cloud platforms (AWS, GCP, or Azure) for model deployment.
- Work on cutting-edge AI and graph-based projects with real-world impact in the financial sector.
- Collaborate with a talented, global team in a supportive and innovative environment.
- Competitive compensation package and comprehensive benefits.
- Opportunities for professional growth and development.
About Us
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