Lead Data Scientist
Serbia/Hyderabad/North Macedonia (Remote)
We’re looking for an experienced Lead Data Scientist to join our Insurtech team and drive impactful, data-driven solutions. In this role, you’ll lead and mentor a team of talented engineers, guiding the development and deployment of scalable machine learning models. You’ll collaborate across teams to structure data, generate insights, and ensure real-world impact. Join us to shape the future of insurance technology through innovation and leadership.
What You’ll Be Doing
- Lead and mentor a team of Machine Learning Engineers, driving the development of scalable, real-world AI solutions.
- Oversee the full ML model lifecycle – from development and training to deployment, monitoring, and maintenance in production.
- Guide the structuring, analysis, and interpretation of data to deliver actionable insights that support business decisions.
- Collaborate with cross-functional teams to align machine learning initiatives with strategic business goals.
- Apply deep expertise in ML and NLP to advance our Intelligent Document Processing platform, including tasks like text extraction, classification, and semantic analysis.
- Implement MLOps best practices to ensure reliable model deployment and performance at scale.
- Stay ahead of emerging technologies, continuously experimenting to enhance our AI capabilities.
- Foster a culture of innovation and communicate complex technical concepts clearly to diverse stakeholders.
What We’re Looking For
- Proven experience as a Lead Data Scientist, Machine Learning Engineer, or in a similar role, with a strong track record of leading and mentoring technical teams.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
- Demonstrated success in leading teams that have designed, deployed, and scaled machine
learning models that deliver measurable business value. - Deep expertise in machine learning, deep learning, and data mining techniques within
enterprise environments. - Hands-on experience with natural language processing (NLP) and data extraction tools.
- Proficiency in Python (or similar languages) and familiarity with libraries such as Scikit-learn, TensorFlow, and PyTorch.
- Strong grasp of MLOps practices, including model lifecycle management and scalable deployment.
- Excellent analytical and leadership skills, with the ability to translate data into actionable
business insights and align ML initiatives with strategic goals. - Prior experience in the insurance domain is a plus, but not required.