
Data Analyst Innovator
4 days ago
At the forefront of applied AI, our team pushes boundaries to create intelligent systems and data platforms that drive business growth.
- Key Responsibilities:
- Develop machine learning models and data-driven features using recommendation systems, NLP, generative AI, and predictive analytics.
- Collect, clean, and analyze structured + unstructured data to uncover insights and support product decisions.
- Rapidly test ideas in notebooks, then work with engineers to productionize models using MLOps practices.
- Design experiments (A/B tests, evaluation pipelines), define success metrics, and continuously improve model performance.
- Partner with cross-functional teams to ensure data and AI capabilities directly support real-world use cases.
What We're Looking for:
- 2–6 years of experience as a Data Scientist / ML Engineer (startup or product environment a plus).
- Strong programming skills in Python; comfort with libraries like Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, or Hugging Face.
- Experience with data pipelines and storage (SQL, NoSQL, or vector databases such as Pinecone, Weaviate, or FAISS).
- Understanding of retrieval-augmented generation (RAG) and generative AI techniques is a plus.
- Familiarity with MLOps, model deployment, and monitoring (Docker, Kubernetes, cloud platforms).
- Strong analytical and communication skills—able to turn data into insights and insights into product decisions.
- Experience with LLM evaluation frameworks or prompt engineering.
- Familiarity with data visualization (e.g., Plotly, D3.js, Tableau).
- Experience working in early-stage startups or venture building environments.
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