Job Description
Job Summary
- We’re looking for a highly proactive Data Scientist with strong experience in Machine Learning (ML) and Generative AI. If you're passionate about building scalable AI-powered applications, deploying ML models into production, and creating impactful learning experiences through AI innovation—this role is for you.
Key Responsibilities:
- Identify and automate data collection from valuable sources for AI and chatbot development.
- Preprocess structured and unstructured data for ML and Generative AI training.
- Develop and fine-tune predictive models and intelligent assistants using GenAI.
- Deploy ML models and chatbots into scalable, web-based production environments.
- Analyze large datasets to drive insights that improve learning experiences.
- Build dashboards to track model performance and data trends.
- Collaborate with cross-functional teams to integrate AI features into platforms.
- Maintain and troubleshoot ETL pipelines supporting data warehouse systems.
- Lead POCs and clearly communicate findings and ideas to stakeholders.
- Stay ahead of the curve on Generative AI trends and tools.
Required Qualifications & Skills:
- Strong background in Machine Learning and AI algorithms.
- Proficient in Python, SQL, and R; Django experience is a bonus.
- Hands-on experience with ETL pipelines, Apache Airflow, and workflow orchestration.
- Familiarity with Generative AI models (e.g., ChatGPT, Claude, Gemini, Mistral).
- Experience using LangChain, LlamaIndex, or LangGraph for GenAI apps.
- Strong statistical, mathematical, and data mining skills.
- Experience with BI tools like Tableau or Looker Studio is a plus.
- Strong analytical mindset, excellent problem-solving and communication skills.
- Product thinking and experience in building end-to-end AI-powered experiences is a strong advantage.
Education & Background
- BSc/BA in Computer Science, Engineering, or related field (Master’s preferred).
- Minimum 2 years in a Data Scientist, ML Engineer, or AI Engineer role.
- Experience working in a tech-driven or startup environment is highly valued.