Data Scientist

Responsibilities:

• Data Exploration & Analysis: Collect, clean, and preprocess data from various sources. Perform exploratory data analysis (EDA) to uncover patterns, trends, and relationships.
• Model Development: Develop, implement, and optimize machine learning models to address specific business problems. Evaluate model performance and refine models as necessary.
• Derive actionable insights from structured and unstructured big data.
• Solve complex business problems by formulating, developing, and interpreting statistical models and analysis.
• Conduct R&D in data science to drive methodology improvement.
• A/B Testing & Experimentation: Design and analyze A/B tests and other experimental methodologies to assess the impact of various interventions.
• Data Visualization: Create compelling visualizations and dashboards to communicate insights and findings to both technical and non-technical stakeholders.
• Reporting: Prepare detailed reports and presentations summarizing findings, methodologies, and implications for internal and external stakeholders.
• Collaboration & Knowledge Sharing: Work closely with cross-functional teams to integrate data insights into program planning and execution. Share knowledge and mentor junior team members in data science best practices.
• Deploying Models & Monitoring: You will be involved in deploying, monitoring, and observability of models in production.
• Continuous Learning: Stay up-to-date with the latest developments in data science, machine learning, and analytics to continuously improve RTV’s data capabilities.

Qualification and Requirements

• Degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• At least three years of experience in data science, analysis, or research, preferably in the nonprofit sector.
• Experience using one or more of the following packages: TensorFlow/Keras, Pytorch Lightning/fastai
• Proficiency in Python programming language.
• Experience with data manipulation tools and libraries (e.g., pandas, NumPy, matplotlib, seaborn etc)
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Knowledge of SQL and experience with relational databases.
• Familiarity with cloud platforms such as AWS, GCP, or AZURE.
• Excellent communication skills with the ability to present complex concepts.
• Experience in data lifecycle management, including collection, analysis, and reporting.

Skills & Abilities:

• Ability to work collaboratively and engage with diverse stakeholders.
• Flexibility to adapt to changing priorities and deadlines.
• Demonstrated knowledge and understanding of the application of Theories of Change (TOC).
• Ability to apply M&E process-based tools, including result-based and participatory monitoring and evaluation, gender analysis frameworks, feasibility studies, data quality assurance, and reporting.
• Strong training & facilitation skills.
• Experience in participatory research within last-mile communities is an advantage.
• Team player with the ability to be self-driven.
• Strong analytical and problem-solving skills.