Lead Data Scientist

About the Role:
As a Lead Data Scientist, you will independently execute specialized data tasks, focusing on model development, data interpretation, and driving forward the data science agenda. You will leverage advanced algorithms and statistical techniques to unearth insights and guide business decisions. This position is suited for self-driven professionals who excel at transforming raw data into strategic assets and are ready to contribute significantly to data science projects.

Responsibilities:
• Lead the development and deployment of advanced machine learning models.
• Perform in-depth data analysis to identify actionable insights.
• Develop and maintain complex data processing pipelines.
• Collaborate with stakeholders to align data science initiatives with business goals.
• Drive feature engineering and selection processes.
• Design and implement scalable data solutions for analytics.
• Conduct exploratory data analysis to explore new opportunities.
• Ensure the robustness and reliability of data science projects.
• Provide guidance on best practices for data science workflows.
• Stay ahead of trends and continuously improve technical skills and knowledge.

Skills:
• Advanced Statistical Methods: Proficient in applying complex statistical techniques.
• Machine Learning Expertise: In-depth knowledge of machine learning algorithms and their practical applications.
• Python/R/SAS: Advanced skills in Python, with knowledge in R or SAS for data analysis.
• Big Data Technologies: Familiarity with big data tools like Spark and Hadoop.
• Data Engineering: Proficiency in building and managing data pipelines.
• Predictive Modeling: Expertise in developing and fine-tuning predictive models.
• Communication: Excellent ability to translate data insights into business strategies.
• Project Management: Strong project management skills to oversee data initiatives.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.