- Company Name
- Humara by 15gifts
- Job Title
- Data Scientist (Full Stack)
- Job Description
-
**Job Title:** Data Scientist (Full Stack)
**Role Summary:**
Mid‑level data scientist embedded in a cross‑functional delivery team building a generative AI product. Responsible for researching, modeling, and developing features that personalize intelligent user interactions, while delivering production‑ready ML solutions end‑to‑end.
**Expectations:**
- Design, train, and deploy NLP‑focused machine‑learning models.
- Write clean, production‑grade Python code and integrate it into a live environment.
- Operate within a professional software engineering setting, adhering to code quality, security, and monitoring standards.
- Collaborate closely with data scientists, product owners, and ML engineers.
- Stay current with cutting‑edge techniques (e.g., reinforcement learning, LLM fine‑tuning) and apply them to improve product performance.
- Respond to production alerts during working hours and contribute to continuous improvement.
**Key Responsibilities:**
- Develop, train, and productionise NLP and language‑understanding models using PyTorch (or TensorFlow).
- Implement and maintain AI services on AWS, leveraging GPU acceleration and containerisation (Docker/ECR).
- Build intelligent guardrails and monitoring for model safety and reliability.
- Create and maintain API services (e.g., FastAPI, Django) and microservice architectures.
- Conduct performance measurement, metric analysis, and documentation of models and pipelines.
- Share knowledge across the team and contribute to best‑practice standards.
**Required Skills:**
- Strong foundation in machine‑learning theory and hands‑on experience with NLP (text embeddings, LLMs, entity/intent recognition).
- Proficient in production‑grade Python development.
- Experience with deep‑learning frameworks: PyTorch, TensorFlow, Scikit‑learn.
- Familiarity with AWS services, GPU acceleration, and container technologies (Docker, ECR).
- Knowledge of microservice design patterns and web frameworks (FastAPI, Django).
- Exposure to reinforcement learning, recommendation systems, supervised/unsupervised methods, and uplift modeling.
- Ability to implement agentic/RAG architectures (beneficial).
- Excellent communication skills for translating technical concepts to non‑technical stakeholders.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field (Master’s preferred).
- No specific certifications required, though certifications in AWS, Machine Learning, or Deep Learning are advantageous.