Senior Data Scientist Team Lead
2 weeks ago
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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.
- Research / Data Analysis jobs
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