Senior Data Scientist Team Lead at PersSol Pty(LTD)

Key Resposibilities

Data Analysis and Modeling:

• Develop and deploy machine learning and artificial intelligence models and algorithms to extract insights, predict outcomes, and optimize processes.
• Conduct in-depth data analysis, data exploration, and data preprocessing to extract valuable information from large datasets.
• Apply statistical techniques and hypothesis testing to validate findings.

Data Strategy and Planning:

• Collaborate with stakeholders to define data-driven objectives and formulate data strategies aligned with business goals.
• Identify key performance indicators (KPIs) and establish data collection and measurement protocols.

Feature Engineering:

• Engineer features and create data pipelines to prepare and clean data for modeling.
• Work with data engineering teams to ensure data availability and quality.

Model Evaluation and Deployment:

• Evaluate model performance and fine-tune models for improved accuracy.
• Deploy models in production environments and monitor their ongoing performance.
• Implement best practices for model version control and management.
• Ensure proven models are integrated into business processes and software products removing the requirement for human intervention to implement the model within their respective businesses.

Cross-Functional Collaboration:

• Collaborate with business analysts, data engineers, and domain experts to understand and address specific business problems.
• Communicate findings and insights to non-technical stakeholders in a clear and actionable manner.

Leadership and Mentorship:

• Provide leadership and mentorship to junior data scientists.
• Participate in knowledge-sharing and training programs to enhance the data science capabilities of the team.
• Foster a collaborative and innovative work environment.

Data Privacy and Compliance:

• Ensure data privacy and compliance with relevant regulations and best practices.
• Develop and enforce data security protocols.

Qualifications:

• Bachelor's or Master's degree in computer science, data science, or a related field.
• Proven experience in data science roles, including hands-on experience with machine learning and statistical analysis and AI
• Proficiency in data analysis and modeling tools and libraries e.g. Python, R
• Strong programming skills and knowledge of data manipulation and visualization.
• Expertise in data preprocessing, feature engineering, and model evaluation.
• Excellent problem-solving and critical-thinking skills.
• Strong communication and interpersonal skills to effectively collaborate with various stakeholders.
• Relevant certifications e.g. Certified Data Scientist etc.