Job Purpose/Position Summary

The Senior Data Lead will use and implement a wide array of statistical, econometric and advanced machine learning models to drive data organization.
This role will require expertise in data modeling, machine learning (ML), deep learning (DL), and agile practices while working with a distributed team.
As a Senior Data Lead, you will drive the development of innovative data solutions and ensure their alignment with business goals.

Responsibilities

• Data Strategy Development: Define and implement data strategy in alignment with business objectives.
• Data Modeling: Design, implement, and optimize complex data models for structured and unstructured data.
• Machine Learning & Deep Learning: Develop, test, and deploy ML/DL models to solve business problems and improve decision-making processes.
• Data Mining & Statistical Analysis: Leverage expertise in data mining, mathematics, and advanced statistical analysis to uncover insights and guide strategic decisions.
• Pattern Recognition & Predictive Modeling: Develop advanced systems for pattern recognition and predictive modeling to forecast trends and optimize processes.
• Statistical Innovation: Research and devise innovative statistical models for advanced data analysis.
• Data Governance: Establish and enforce data quality and security standards.
• Insights and Implementation: Implement data-driven insights to enhance decision-making and business performance understanding strategic business goals and anticipate analytical needs to support and measure business decisions.
• Research-Oriented Collaboration: Thrive in a dynamic, research-focused group with several concurrent projects, contributing to innovative solutions and high-impact outcomes.
• Industry Awareness: Stay updated on the latest technical and industry developments to identify opportunities for smarter, more efficient business processes.
• Team Leadership: Lead a remote, cross-functional team of data scientists, analysts, and engineers. Mentor junior members to promote professional growth.
• Stakeholder Communication: Communicate findings, insights, and recommendations clearly to all stakeholders, ensuring alignment and understanding.
• Agile Development: Drive the adoption of agile methodologies, ensuring iterative progress and the delivery of high-quality solutions.
• Collaborate Across Teams: Work closely with product design and engineering teams to understand their needs and translate them into actionable data solutions.

Technical Expertise

• Proven experience in data modeling, database design, and optimization.
• Advanced understanding of statistical techniques, data mining, and their application in business contexts.
• Expertise in designing and implementing pattern recognition systems and predictive models.
• proficiency in ML/DL frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Expertise in programming like Python, R, or Java.
• Experience in big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).
• Experience with SQL and NoSQL databases.

Qualification

• Good analytical and problem-solving abilities.
• A data-driven mindset with excellent analytical and critical thinking abilities.
• Comfortable and effective working in a fast-paced, research-oriented group with multiple simultaneous projects.
• Ability to communicate complex data in a simple, actionable way.
• Bachelor's degree (or equivalent) in Statistics, Applied Mathematics, Computer Science or Engineering, Data Science, or a related discipline. A Master's degree or PhD is a plus.