- Company Name
- SoHo Dragon
- Job Title
- Data Scientist / AI engineer
- Job Description
-
Job Title: Data Scientist / AI Engineer
Role Summary:
Design, develop, validate, and deploy advanced generative, recommender, and predictive AI models to create business value. Partner with product and AI leadership to identify opportunities, conduct rigorous statistical analysis, and integrate models into decision‑making processes.
Expectations:
• Deliver scalable, high‑performance AI engines within defined project timelines.
• Apply state‑of‑the‑art research in NLP, predictive analytics, and information retrieval.
• Maintain model accuracy and performance through rigorous testing, A/B experimentation, and continuous monitoring.
• Align AI solutions with business objectives and regulatory constraints in a fast‑moving environment.
Key Responsibilities:
1. Collaborate with Head of AI and Product Manager to uncover data‑driven opportunities.
2. Lead end‑to‑end design, development, validation, and deployment of AI engines.
3. Perform advanced statistical analysis, identify trends, and generate actionable insights.
4. Implement A/B testing frameworks to evaluate model quality and impact.
5. Coordinate cross‑functional teams to integrate models, design monitoring tools, and ensure data quality.
6. Drive AI R&D agenda, champion best‑practice methodologies, and stay current on industry advancements.
Required Skills:
- MS/PhD in Computer Science, Electronics, or related field, or equivalent experience.
- 3+ years of applied AI/ML development and deployment, preferably in financial services.
- Proficiency in Python with libraries: pandas, Spark, scikit‑learn, TensorFlow, PyTorch, LangChain, LlamaIndex.
- Deep expertise in generative AI, NLP, supervised learning, reinforcement learning, and agentic AI.
- Extensive experience with Azure Data Factory; familiarity with AWS SageMaker and Azure Machine Learning.
- Strong MLOps/LLMOps knowledge and practice.
- Ability to merge and transform heterogeneous data sources for AI input.
- Agile methodology experience, strong communication, and stakeholder collaboration.
- Analytical mindset, problem‑solving skills, and data bias awareness.
Required Education & Certifications:
- Minimum Master’s degree in Computer Science, Electronics, Statistics, Mathematics, or related discipline (PhD preferred).
- Certifications in Azure Data Engineering, MLOps, or equivalent are a plus.