Director/VP - Data Science - FinTech (12-18 yrs)

Roles and Responsibilities:

- Develop and articulate a long term vision for the data science function, aligning it with companies strategic goals to ensure impactful, business-oriented outcomes.

- Lead the effort to instill a data-driven mindset across the organization, championing the use of data science to make critical business decisions and maximize value.

- Lead and drive data science initiatives, providing strategic guidance and technical expertise to the team.

- Apply advanced data science methodologies, mathematics, and machine learning techniques to solve complex and strategic business problems.

- Collaborate closely with cross-functional teams, including engineers, product managers, and business stakeholders, to develop and deploy cutting-edge data science solutions.

- Oversee the integration of compliance and regulatory requirements into data science processes, ensuring models and analyses meet all necessary standards.

- Identify the right problems to solve for the organisation with the highest ROI

- Present findings, insights, and strategic recommendations to senior stakeholders, influencing key business decisions.

- Identify key metrics and develop executive-level dashboards to monitor performance and provide actionable insights.

- Oversee multiple projects simultaneously, ensuring high-quality deliverables within defined timelines.

- Mentor and guide junior data scientists, fostering their professional growth and promoting a culture of innovation and excellence.

- Continuously explore and implement advanced data science methodologies and emerging technologies to enhance solutions.

- Collaborate with research teams and stay updated with the latest advancements in the field of data science.

Mandatory Qualifications:

- 12-18 years of experience in a data science role, with a proven track record of delivering impactful solutions and building and managing high performance teams.

- Advanced degree (Master's or Ph.D.) in a quantitative field, such as Computer Science, Statistics, Mathematics, or related disciplines.

- Extensive expertise in advanced machine learning techniques, statistical analysis, and mathematical modeling.

- Mastery of programming languages such as Python, R, and Scala, with experience in building scalable and efficient data science workflows.

- ML-Engineering/ML-Ops knowledge, awareness and proficiency of Kubernetes, nosql, redis etc.

- Vast experience with big data processing frameworks (e.g., Hadoop, Spark) and deep learning frameworks (e.g., TensorFlow, PyTorch).

- Strong leadership skills, with the ability to guide and inspire a team, prioritize tasks, and drive successful outcomes, excellent communication and presentation skills.

- Drive collaboration between data science, product management, and engineering teams to ensure alignment on project goals and seamless integration of machine learning solutions into products.

- Facilitate regular cross-functional meetings and workshops to identify key business challenges, drive data democratization, and brainstorm innovative and cost effective solutions.

- Deep experience with cloud platforms (e.g., AWS, Azure, GCP) and their data science tools and services.

- A passion for continuous learning and staying up-to-date with the latest advancements in data science.

- Demonstrated ability to think strategically, solve complex problems, and deliver innovative solutions.