Urgent: VP

The VP - Data Science will oversee the development and implementation of data-driven solutions across the organization. The role involves leading a team of data scientists, collaborating with cross-functional teams, and delivering actionable insights to support business decisions. The ideal candidate will have a deep understanding of machine learning, statistical modeling, and advanced analytics to drive innovation and solve complex business challenges. Key Responsibilities: Data Science Leadership: - Lead the data science team to develop advanced analytical models and machine learning algorithms to address business problems. - Provide technical guidance and mentorship to data scientists, fostering an environment of continuous learning and development. - Collaborate with business stakeholders to understand their challenges and objectives, translating them into data science projects. Model Development and Deployment: - Design and implement predictive models, recommendation engines, and optimization algorithms using machine learning and statistical techniques. - Oversee the end-to-end lifecycle of models, including data collection, feature engineering, model development, validation, and deployment. - Ensure that models are scalable, efficient, and deployed into production with proper monitoring and maintenance processes. Data Strategy and Innovation: - Define the data science strategy and roadmap aligned with the organization’s business goals. - Identify opportunities to leverage data science and advanced analytics to enhance decision-making, optimize processes, and improve customer experiences. - Stay up-to-date with the latest trends and advancements in data science, machine learning, and artificial intelligence to keep the team and organization at the cutting edge. Collaboration with Cross-Functional Teams: - Work closely with data engineers, software developers, and business analysts to ensure data science solutions are well-integrated into the broader data ecosystem. - Collaborate with product, marketing, operations, and finance teams to develop solutions that enhance business performance. - Act as the primary point of contact for data science initiatives, presenting findings and recommendations to senior leadership and key stakeholders. Data Quality and Governance: - Ensure data quality and integrity across all data science initiatives by working with data engineers to implement proper data governance frameworks. - Define and enforce best practices for data science methodologies, including version control, reproducibility, and documentation of models. - Work closely with IT and data management teams to ensure data infrastructure supports the team’s analytical needs. Performance Monitoring and Reporting: - Develop dashboards and performance metrics to track the success of models and provide insights into ongoing data science projects. - Present findings and model outcomes to business stakeholders, making recommendations for business decisions based on data-driven insights. - Continuously monitor model performance in production, implementing improvements as necessary. Qualifications: - Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or related field. Experience: - 8+ years of experience in data science, with at least 4 years in a leadership role. - Proven experience leading a team of data scientists, delivering end-to-end data science solutions, and driving business outcomes. - Strong background in machine learning, statistical modeling, data mining, and advanced analytics. Technical Skills: - Proficiency in programming languages such as Python or R for data analysis and model development. - Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). - Strong SQL skills for data manipulation and extraction from large-scale data sets. - Hands-on experience with big data technologies such as Hadoop, Spark, or cloud platforms (AWS, Azure, GCP). - Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib). Leadership and Communication: - Ability to translate complex technical concepts into actionable insights for non-technical stakeholders. - Excellent leadership skills with a proven ability to manage, mentor, and develop a team. - Strong presentation skills to articulate data-driven insights to senior management. Preferred Skills: - Experience with deep learning techniques, NLP, computer vision, or reinforcement learning. - Familiarity with MLOps and model deployment in production environments. - Knowledge of cloud-based data platforms and services for large-scale machine learning solutions. - Experience working in an agile environment, with strong project management skills. Soft Skills: - Strong problem-solving and analytical thinking. - Excellent communication and collaboration skills. - A passion for innovation and continuous improvement in data science practices.