Job Responsibilities:
- Lead all stages of data preparation, analytics & AI product development life cycle: from problem identification, conceptualization, prioritization to solution development and delivery. Contribute to hands-on development of data & analytics solutions.
- Collaborate with business and technology partners to co-create solutions, work on human-centered design, frictionless services, and meaningful engagement.
- Deliver products and solutions in a timely, proactive, and entrepreneurial manner. Accelerate solution delivery using re-usable frameworks, prototypes and hackathons.
- People leadership: talent acquisition, coaching and mentoring team
- Ensure the security and privacy of sensitive data used in analytics solutions, and comply with relevant regulations such as GDPR
- Participate in research projects aimed at advancing the field of data science and analytics, and presenting findings at conferences or publications. Institutionalize best practices, contribute to research and experimentation efforts.
- Represent the firm at industry events, conferences, and workshops, presenting research findings and sharing best practices with other experts in the field.
Education, Technical Skills & Other Critical Requirement:
- 6-12 years of relevant experience in AI/ analytics product & solution delivery
- Bachelor's/Master's degree in an information technology/computer science/Statistics/ Economics or equivalent fields experience.
- Strong understanding of Machine Learning and Deep Learning concepts, with a focus on Natural Language Processing.
- Proficiency in Python programming language, with experience using libraries like PyTorch for deep learning tasks.
- Familiarity with Elastic stack (Elasticsearch, Logstash, Kibana) for data management and analysis.
- Experience in optimizing algorithms and time series forecasts.
- Knowledge of prompt engineering techniques to improve model performance.
- Ability to prototype applications using Streamlit or similar tools.
- Experience working with large and complex internal, external, structured and unstructured datasets.
- Model development and deployment in cloud; Familiarity with Github, CI/CD process, Docker, Containerization & Kubernetes.
- Developing and maintaining detailed technical documentation.
- Solution Engineering and Consultative skills: Strong conceptual and creative problem-solving skills
- Familiarity with agile methodologies & tools.
- Good written, verbal communication skills and presentation skills; engage in meaningful manner with variety of audience: business stakeholders, technology partners & practitioners, executive and senior management.
- Industry knowledge about emerging AI trends, AI tools and technologies
