Data Analytics Intern at Kenya Association of Manufacturers

Job Purpose:

Kenya Association of Manufacturers (KAM) carries out fact-based research advocacy on behalf of its members. To unleash the power of data science in transforming advocacy and policy making, KAM is seeking a passionate and skilled Data Scientist to join our policy advocacy team as an intern. The ideal candidate will leverage data analytics, machine learning, and artificial intelligence, statistical modeling to drive insights that support advocacy efforts. This role involves working closely with Policy, and Regulatory Advocacy team to transform complex data into actionable insights that influence policy for the benefit of KAM Members.

Duties and Responsibilities

• The specific duties and responsibilities will include, but are not limited to the following: -
• Develop and apply data-driven methodologies to support advocacy campaigns and policy initiatives.
• Collect, clean, and analyze large datasets from various sources, including surveys, social media and public records and other relevant secondary data sources.
• Utilize statistical and machine learning models to identify trends, correlations, and impact metrics.
• Design and build dashboards, reports, and visualizations to communicate findings effectively to diverse stakeholders.
• Collaborate with cross-functional teams within the Policy and Regulatory Advocacy.
• Provide quantifiable metrics for measuring the impact of advocacy campaign.
• Conduct sentiment analysis, predictive modeling, and network analysis to enhance advocacy strategies.
• Stay up to date with advancements in data science and analytics, ensuring the use of best practices.
• Present findings in a clear and compelling manner to both technical and non-technical audiences.
• Perform any other duties as may be assigned by the Chief Executive from time to time

Qualifications:

• Bachelor’s degree in Data Science.
• 2+ years of experience in data science, analytics, or a related field, preferably in advocacy or public policy.
• Proficiency in Python, R, SQL, or other data analysis tools.
• Experience with data visualization tools such as Tableau, Power BI, or D3.js.
• Strong knowledge of statistical methods, machine learning techniques, and natural language processing.
• Familiarity with web scraping, APIs, and data pipeline development.
• Ability to interpret complex data and translate insights into strategic recommendations.
• Excellent communication skills and ability to work in a multidisciplinary team.

Personal attributes:

• Effective organizational skills, team player, keen attention to detail, and multitasking ability.
• The ability to work as part of a team and on your initiative