About the Role
We are seeking a Data Scientist to extract actionable insights from our data and drive data-driven decision-making. This role will play a pivotal part in analyzing data, building predictive models, and providing valuable insights to support our business objectives. The Data Scientist is responsible for leveraging data analysis, statistical modeling, and machine learning techniques to extract knowledge and insights from data to inform strategic decisions and solve complex business problems. This role covers data analysis, statistical modeling, machine learning, and the development of data-driven solutions. The Data Scientist will be a key member of our AI Economics Team, collaborating with policy consultants, data engineers, data analysts, product owners, and stakeholders to provide valuable insights from data. The start date for this position is January 2025 and it reports to the AI Economics Lead.
Responsibilities
- Data Analysis: Analyze data to identify trends, patterns, and insights that can drive business decisions.
- Statistic Modelling: Develop statistical models to analyze and interpret data and generate actionable insights.
- Machine Learning: Apply machine learning algorithms to solve complex business problems and build predictive models.
- Data Visualization: Create data visualizations and reports to communicate findings effectively.
- Hypothesis Testing: Conduct hypothesis testing to validate and prove or disprove hypotheses based on data analysis.
- Data Quality: Work with data engineers to ensure data quality and consistency for analysis.
- Documentation: Maintain clear documentation of data analysis, modeling processes, and model performance.
Requirements
Technical Skills
- Data Analysis Tools: Proficiency in data analysis tools such as Python, R, or similar.
- Statistical Modelling: Strong knowledge of statistical modeling techniques and tools.
- Machine Learning: Proficiency in data visualization tools like Tableau, Power BI, or matplotlib.
- Hypothesis Testing: Understanding of hypothesis testing techniques and statistical significance.
- API Frameworks: Strong command of API frameworks such as fast API type, postman, swagger.
- SQL: Proficiency in SQL for data retrieval and transformation.
Qualifications
- Education: Bachelor's/Master's degree in Data Science, Statistics, Economics, Computer Science, or a related field.
- Experience: 2+ years of experience in data science, with a focus on data analysis, statistical modeling, and machine learning.
Personal Attributes
- Problem Solving: Proven ability to troubleshoot and address complex data analysis and modeling challenges.
- Analytical Mind: Capable of understanding complex data and business problems and extracting insights.
- Communication: Effective communication skills to convey complex data findings to non-technical stakeholders.
- Detail Orientated: Attention to detail in data analysis, modeling, and documentation.
- Agility: Flexibility to adapt to changing data requirements and priorities.
- People Orientated: Keeping individual authenticity, build meaningful connections, and firmly believe that we are stronger as One team.
- Empowerment: Take ownership in work, making decisions, and initiating internal projects.
- Foresight: Be a forward thinker who demonstrates hyper-awareness of market trends and looks beyond the present to provide innovative and sustainable solutions.
- Work Ethic: Foster positive culture, built on integrity, transparency, and accountability, while always striving for excellence.