Key Responsibilities
- Data Analysis and Interpretation
- Analyse large and complex datasets to derive actionable insights.
- Interpret data trends and patterns to inform business decisions.
- Design and implement data experiments to validate hypotheses.
- Statistical Modelling and Machine Learning
- Develop and deploy advanced statistical models and machine learning algorithms.
- Optimize models for accuracy, efficiency, and scalability.
- Stay updated with the latest developments in machine learning and AI.
- Experience with advanced analytics techniques beyond traditional statistical models, such as deep learning or natural language processing.
- Data Engineering
- Collaborate with data engineers to ensure data quality and integrity.
- Develop and maintain data pipelines for efficient data processing.
- Work with large-scale databases and distributed computing environments.
- Business Collaboration
- Work closely with cross-functional teams to understand business requirements.
- Translate business needs into data science projects and solutions.
- Present findings and recommendations to stakeholders and senior management.
- Emphasize the importance of business acumen to understand and contribute to the company's strategic goals through data-driven insights.
- Mentorship and Leadership
- Mentor and provide guidance to junior data scientists and analysts.
- Lead data science projects from inception to deployment.
- Promote best practices in data science within the team.
- Innovation and Research
- Keep in touch with the latest trends and advancements in data science and related fields.
- Drive innovation within the team by exploring new methodologies and technologies.
Qualifications
- Education
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related field.
- Experience
- Minimum of 5 years of experience in data science, machine learning, or related fields.
- Proven track record of successfully delivering data science projects.
- Technical Skills
- Proficiency in programming languages such as Python, R, or Scala.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong knowledge of SQL and experience with relational databases.
- Familiarity with big data technologies (e.g., Hadoop, Spark).
- Experience with AWS cloud platform.
- Analytical Skills
- Strong problem-solving skills and analytical thinking.
- Ability to work with complex datasets and perform statistical analysis.
- Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn).
- Soft Skills
- Excellent communication and presentation skills.
- Ability to work collaboratively in a team environment.
- Strong organizational skills and attention to detail.
- Preferred Qualifications
- Experience working in regulated industries, such as financial services or legal.
- Experience with cloud platforms - GCP and Azure.
Publications or contributions to the data science community.
