
Data Analyst Manager
1 week ago
Data Scientist Role
We are seeking a highly skilled professional to join our team as a Data Scientist. This role involves working at the intersection of software development, machine learning, and data analysis, delivering real-world impact from day one.
You will develop tools, infrastructure, and applications that transform raw data into actionable insight. You will collaborate closely with analysts, quants, and operations teams to build production-ready systems that drive decision-making across the organization.
Main Responsibilities:
- Design and Build Robust Software Systems: Develop maintainable software systems to support data pipelines, analytics, and AI applications.
- Collaborate with Domain Experts: Work with domain experts to scope, build, and iterate on AI-driven tools tailored to business needs.
- Develop Efficient Data Pipelines: Use Python, SQL, and modern libraries to develop efficient data ingestion, transformation, and validation pipelines.
- Integrate Large Language Models: Integrate large language models (LLMs) and generative AI APIs (e.g., OpenAI, HuggingFace) into internal tooling.
- Create Clean User Interfaces: Create clean, intuitive user interfaces and data visualizations with libraries like Plotly and Dash.
- Optimize Database Performance: Optimize database access and performance for large structured and semi-structured datasets.
- Ensure Scalability and Security: Ensure tools are scalable, secure, and aligned with end-user workflows and UX needs.
- Take Projects to Production: Take projects from concept to production, including testing, documentation, deployment, and iteration.
Key Qualifications:
- Strong Programming Skills: Proficiency in Python, with exposure to software engineering best practices (version control, testing, modular code).
- Proficiency with SQL: Familiarity with relational databases and SQL.
- Experience with Data Pipelines: Experience working with data pipelines, ETL workflows, and data wrangling techniques.
- Familiarity with ML Frameworks: Familiarity with ML frameworks such as PyTorch, and data libraries like Pandas and Numpy.
- Exposure to Generative AI: Exposure to generative AI or LLM APIs and frameworks (e.g., OpenAI, Cohere, HuggingFace Transformers, DSPy, LangChain).
- Understanding of Machine Learning: Understanding of fundamental machine learning and data science concepts.
- Strong Communication Skills: Strong written and verbal communication skills, especially in explaining complex technical topics to diverse stakeholders.
- User-Focused Mindset: A user-focused mindset: you care about who's using your tools and how to make them intuitive, reliable, and useful.
- Team-Oriented: A team-oriented approach: you work well with others, ask great questions, and contribute to a collaborative culture.
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