Data Scientist (Specialist)

Job Description

The Data Scientist will drive RURA's evidence-based regulatory approach by developing predictive models, conducting advanced statistical analyses, and building machine learning solutions to address complex regulatory challenges across Rwanda's regulated sectors. This role involves designing and implementing sophisticated analytical frameworks, developing automated insights systems, and creating data-driven solutions that enhance regulatory effectiveness and policy decision-making. The scientist will collaborate with analysts, engineers, and policy teams to translate complex business problems into mathematical solutions and deliver scalable, production-ready models aligned with RURA's strategic objectives.

Responsibilities

KEY RESPONSIBILITIES

• Develop predictive and statistical models to support evidence-based regulatory decision-making, using machine learning, time-series analysis, and other advanced analytics techniques.

• Work with structured and unstructured data from a variety of sources (e.g., sensor data, administrative records, operational systems, APIs) to generate actionable insights.

• Collaborate with analysts, engineers, and policy teams to frame analytical problems, define modeling objectives, and interpret results in support of regulatory strategy.

• Design and conduct experiments or simulations to evaluate regulatory policies, sector performance, or service delivery outcomes.

• Build reusable analytical tools, scripts, and models that can be deployed and maintained across different regulatory projects and domains.

• Communicate complex analytical findings clearly and effectively to both technical and non-technical stakeholders through visualizations, reports, and presentations.

• Prototype and test innovative data science solutions that explore new ways of measuring, forecasting, or detecting regulatory risks, opportunities, and compliance issues.

• Contribute to RURA’s data ecosystem by improving data accessibility, enhancing model explainability, and fostering data literacy within teams.

• Evaluate the impact of regulatory interventions using causal inference techniques (e.g., A/B testing, difference-in-differences, regression discontinuity).

• Ensure ethical and responsible use of data science, including compliance with Rwanda’s data protection laws and the agency’s principles of fairness, accountability, and transparency.

• Document models, assumptions, methodologies, and results to ensure reproducibility and knowledge transfer.

• Stay up to date with trends in data science, regulation, and sector-specific analytics, and apply best practices to improve RURA’s analytical capabilities.

Requirements

Education and Experience

• A Master's degree in data science, statistics, applied mathematics, computer science, econometrics, or a related quantitative field, with 1 year of professional experience applying data science methods in a research, regulatory, public policy, or operational context. or

• A Minimum of a Bachelor's degree in data science, statistics, applied mathematics, computer science, econometrics, or a related quantitative field, with a minimum 3 years of professional experience applying data science methods in a research, regulatory, public policy, or operational context.

SKILLS AND COMPETENCIES

• Statistical & Machine Learning Expertise: Strong foundation in descriptive statistics, predictive modeling, clustering, classification, time-series forecasting, and causal inference.

• Programming for Data Science: Proficient in Python or R for data cleaning, transformation, analysis, and modeling using packages such as pandas, scikit-learn, statsmodels, numpy, ggplot2, or dplyr.

• Data Visualization: Ability to present complex data through intuitive visualizations using tools like Power BI, Tableau, matplotlib, seaborn, or plotly.

• SQL and Data Querying: Skilled in writing complex SQL queries and working with both OLAP and OLTP databases (e.g., ClickHouse, PostgreSQL, MySQL).

• Problem Framing & Hypothesis Testing: Capable of defining research questions, developing hypotheses, and selecting appropriate analytical methods to test them.

• Model Development & Validation: Experience in training, tuning, validating, and deploying statistical and machine learning models for practical applications.

• Data Wrangling & Feature Engineering: Able to work with messy, incomplete, or unstructured data and derive meaningful features for modeling.

• Communication: Strong written and verbal communication skills, with the ability to present findings clearly to non-technical audiences and influence policy or operational decisions.

• Reproducibility & Documentation: Knowledge of tools for documenting code, workflows, and analysis pipelines using Jupyter, RMarkdown, Git, or Notion.

• Ethical & Responsible AI Awareness: Understanding of data ethics, model fairness, bias mitigation, and compliance with Rwanda’s data protection regulations.

• Team Collaboration: Experience working in cross-functional teams (e.g., with engineers, analysts, and policy experts) and supporting shared objectives.

• Continuous Learning: Demonstrates intellectual curiosity and a commitment to staying current with new tools, algorithms, and regulatory applications of data science.

CANDIDATE PROFILE

• Analytical Thinker: Approaches complex problems with curiosity and rigor, using data to uncover patterns, trends, and insights that can guide regulatory action.

• Mission-Driven: Motivated by the public good and passionate about applying data science to improve services, compliance, and outcomes across regulated sectors in Rwanda.

• Collaborative by Nature: Works well with diverse teams—ranging from data engineers to policy experts—and values shared learning and cross-sector engagement.

• Detail-Oriented: Pays close attention to data accuracy, model validity, and methodological soundness, particularly when findings will impact national policy or regulation.

• Clear Communicator: Can translate complex analytical results into clear, actionable insights tailored to non-technical audiences, including decision-makers and stakeholders.

• Self-Learner & Innovator: Actively keeps up with advances in data science tools, methods, and sector-specific applications; eager to pilot new approaches where appropriate.

• Ethically Minded: Understands the importance of responsible data use, including fairness, transparency, privacy, and alignment with Rwanda’s data protection laws.

• Systems-Oriented: Thinks beyond individual analyses and contributes to the broader data infrastructure, governance, and analytical maturity of RURA. 

• Strong statistical and analytical skills, with proven experience building predictive models, clustering, classification, regression, time-series forecasting, or other machine learning techniques.

• Proficiency in programming languages such as Python or R for data analysis, modeling, and visualization (e.g., scikit-learn, pandas, NumPy, tidyverse, caret).

• Experience working with relational and non-relational databases, and writing advanced SQL queries for data extraction and manipulation.

• Familiarity with real-world data challenges, including missing values, messy formats, and integrating data from disparate sources.

• Ability to clearly communicate analytical findings, both in writing and verbally, to technical and non-technical audiences.

• Knowledge of data visualization tools and libraries such as Power BI, Tableau, matplotlib, ggplot2, or seaborn.

• Understanding of data ethics, privacy, and protection standards, especially Rwanda’s data protection law and responsible AI principles.

• Familiarity with cloud-based tools, APIs, or notebooks (e.g., Jupyter, Google Colab, SageMaker) is an advantage.

• Experience collaborating on interdisciplinary projects, particularly those involving policy, research, or digital transformation initiatives.