Role Overview:

As the Director Data Science - AI, based in Bangalore, you will lead a team of talented data scientists and engineers, driving the development and implementation of cutting-edge AI solutions. You will collaborate closely with product managers, engineering teams, and business stakeholders to identify opportunities to leverage AI and machine learning to improve our products, enhance customer experiences, and drive business growth. Your work will directly impact the company's strategic direction, ensuring we remain at the forefront of innovation in the AI space.

Key Responsibilities:

- Define and execute the AI strategy, aligning it with overall business objectives and product roadmaps, to maximize the impact of AI initiatives.

- Lead and mentor a team of data scientists and engineers, fostering a culture of innovation, collaboration, and continuous learning, to build a high-performing AI organization.

- Drive the development and deployment of machine learning models and AI-powered solutions, working closely with engineering teams, to deliver impactful products and features.

- Collaborate with product managers and business stakeholders to identify and prioritize AI opportunities, ensuring alignment with business needs and customer requirements.

- Conduct research and experimentation to explore new AI techniques and technologies, staying abreast of the latest advancements in the field, to maintain a competitive edge.

- Communicate complex technical concepts and findings to both technical and non-technical audiences, influencing decision-making and driving adoption of AI solutions.

- Ensure the ethical and responsible use of AI, adhering to industry best practices and regulatory requirements, to maintain trust and transparency.

Required Skillset:

- Demonstrated ability to lead and manage a team of data scientists and engineers, fostering a collaborative and innovative environment.

- Proven expertise in developing and deploying machine learning models and AI-powered solutions, utilizing a variety of techniques and tools.

- Strong understanding of statistical modeling, data mining, and machine learning algorithms, with the ability to apply them to real-world problems.

- Deep knowledge of Natural Language Processing (NLP) techniques and applications, including text classification, sentiment analysis, and machine translation.

- Excellent communication and presentation skills, with the ability to effectively convey complex technical concepts to both technical and non-technical audiences.

- Ability to collaborate effectively with cross-functional teams, including product management, engineering, and business stakeholders.

- Possess a Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field.

- Adaptable to a dynamic and fast-paced environment, thriving in a hybrid work setup.