Identify valuable data sources and automate data collection for AI and chatbot development.
Preprocess structured/unstructured data for training ML and Generative AI models.
Analyze large datasets to uncover trends and enhance learning experiences.
Build and fine-tune predictive models and chatbot assistants using Generative AI.
Deploy AI models and chatbots to web-based production environments with scalability in mind.
Visualize insights and model performance via clear, actionable dashboards.
Collaborate with engineering and product teams to integrate AI into the platform.
Implement AI assistants with focus on NLU, personalization, and ongoing learning. Maintain and investigate ETL pipelines that feed into the data warehouse.
Create proof-of-concept (POC) solutions and present ideas clearly to management and stakeholders.
Stay up-to-date with Generative AI trends to improve interactive learning tools.
KNOWLEDGE, SKILLS AND ABILITIES:
Strong understanding of Machine Learning, AI algorithms, and operations research techniques.
Proficient in Python, SQL, and R; familiarity with Django is a plus.
Experience with BI tools such as Tableau or Looker Studio, and a solid foundation in data mining.
Hands-on experience with data pipelines and workflow orchestration tools like Apache Airflow.
Solid math and statistical background (e.g., statistics, algebra, probability).
Strong analytical thinking and a solid business acumen to translate data into strategic insights.
Excellent problem-solving, communication, and presentation skills.
Familiarity with Generative AI models such as ChatGPT, Gemini, Claude, or Mistral.
Experience working with Generative AI frameworks like LangChain, LlamaIndex, or Langgraph for building AI-powered applications.
Comfortable experimenting with emerging AI tools and applying them in practical, user-centric applications.
Experience in product design and ownership is a strong plusespecially in building AI-powered user experiences from concept to deployment.
EDUCATION AND EXPERIENCE:
BSc/BA in Computer Science, Engineering, or a related field; a graduate degree in Data Science, AI, or a relevant discipline is preferred.
2+ years of hands-on experience as a Data Scientist, Data Engineer, Machine Learning Engineer, or Big Data Specialist.
Experience working in a technology-driven or startup environment is an advantage.
Experience as an AI Engineer or in developing AI-driven applications is a strong plus.
