Lead Data Scientist

Job Summary:

We are seeking a highly skilled Lead Data Scientist with 7-10 years of experience in Data Science, Machine Learning, Artificial Intelligence, Statistics, and Deep Learning. The ideal candidate will be responsible for leading data-driven initiatives, mentoring a team of data scientists, and collaborating with cross-functional teams to develop innovative solutions that drive business value.

Key Responsibilities:

Strategy Development: Design and implement a comprehensive data science strategy aligned with organizational goals, focusing on leveraging data for actionable insights.

Team Leadership: Lead and mentor a team of data scientists and analysts, fostering a culture of innovation and continuous improvement. Provide guidance on best practices in data science and machine learning.

Project Management: Oversee the end-to-end development of data science projects, including problem definition, data collection, model development, and deployment.

Collaboration: Work closely with stakeholders across various departments to identify business challenges and opportunities for data-driven solutions. Facilitate cross-functional collaboration to ensure alignment on project goals.

Model Development: Utilize advanced statistical methods and machine learning algorithms to develop predictive models and analytical solutions. Ensure models are robust, scalable, and maintainable.

Data Integration: Manage the integration of data from multiple sources, ensuring data quality and accessibility for analysis.

Performance Monitoring: Establish metrics and monitoring systems to evaluate model performance and business impact. Continuously refine models based on feedback and new data.

Knowledge Sharing: Promote data literacy within the organization by conducting workshops and training sessions on data science methodologies and tools.

Qualifications:

Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
7-10 years of relevant experience in data science, with a strong focus on machine learning and artificial intelligence.
Proficiency in programming languages such as Python, R, or Java, and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
Strong understanding of statistical methods, deep learning frameworks (e.g., TensorFlow, PyTorch), and machine learning algorithms.
Excellent problem-solving skills and the ability to communicate complex concepts to non-technical stakeholders.
Experience with cloud platforms (e.g., AWS, Azure) and data visualization tools (e.g., Tableau, Power BI) is a plus.