Data Scientist

Purpose of the Position

BroadReach Group, in partnership with Uganda’s National Drug Authority (NDA), seek to employ a Data Scientist to contribute towards the Grand Challenges Program: Strengthening African National Regulatory Authorities Data Systems to Enhance and Track Performance (https://gcgh.grandchallenges.org/challenge/strengthening-african-national-regulatory-authorities-data-systems-enhance-and-track)

The focus of this role is monitoring key performance indicators (KPIs) and metrics related to the institutional performance in ensuring safety, efficacy, and regulatory compliance of medicines. Furthermore, your expertise in data analysis will be essential in evaluating the performance of all regulatory functions to ensure public health and safety. Furthermore, this role will support the transition from the current paper-based system to the new KPI monitoring tool and support processes related to setting up a Data Resource Center.

Key Accountabilities

• Drive data mining and analytics to strengthen decision-making across the organization.
• Map and analyze how existing data can be leveraged to support the organization’s goals.
• Serve as a liaison between users and system developers, translating user needs into technical solutions.
• Develop and maintain data models that optimize data storage and retrieval, improving overall system efficiency.
• Enhance data collection procedures to capture relevant information for analytics.
• Provide actionable insights from data to improve system functionality, user experience, and business processes.
• Oversee data processing, cleansing, and verification for integrity and accuracy.
• Use statistical methods, machine learning algorithms, and other advanced analytics techniques to derive meaningful insights from large datasets.
• Identifying and executing ad-hoc analysis for both internal and external stakeholders and presenting results in a clear manner
• Data Governance & Quality: Implement best practices for data governance, security, and privacy in line with regulatory requirements Ensure the integrity, accuracy, and consistency of data across the system.
• KPI Monitoring: Develop, track, and analyze KPIs and metrics related to drug safety, clinical trial outcomes, and regulatory compliance to provide insights that inform decision-making.
• Reporting and Visualization: Create dashboards and comprehensive reports to effectively communicate findings on KPIs to stakeholders, ensuring that the data is accessible and actionable.
• Regulatory Support: Collaborate with regulatory officers to utilize KPI insights in the review process for regulatory decisions in different regulatory functions
• Performance Improvement: Identify opportunities for process enhancements based on KPI analysis and provide recommendations to improve regulatory efficiency and effectiveness.
• Research Support: Contribute to research projects by providing statistical analysis, methodology design, and interpretation of results.
• Train managers and other decision makers to use data for decision making.
• Support IT, product development, and business development teams to ensure data science solutions align with the broader goals of the project.
• Communicate findings, model performance, and analysis results to non-technical stakeholders in a clear and understandable manner.
• Support set up and day to day running of the institutional Data Resource Center

Qualifications

Essential qualifications

• Degree in Computer Science, Mathematics, Statistics, Physics, Data Science or related field.
• Training in Data Science and Use of Data Languages.

Desirable qualifications

• Masters degree in Data Science, Biostatics or Epidemiology

Experience & Skills

• 3-6 years of relevant data science experience in a public health or government setting
• 3+ years of experience in data analysis, with a focus on KPI monitoring in a regulatory or similar environment, clinical research, or the pharmaceutical industry.
• Proven experience in handling complex big data and strong technical skills in data mining and information extraction
• Ability to continuously improve the quality and integrity of data and information including accuracy and relevance to the business
• Prior experience in using Machine Learning algorithms for solving complex and diverse product use cases
• Demonstrated success in using analytics to drive the understanding, growth and success of a product
• Hands-on Experience with statistical software packages (R, SPlus, SaaS), programming languages (SQL, Python or JAVA) and Experience with statistical models for multivariate testing, time series analysis, logistic regression and linear/non-linear regression
• Experience with data visualization tools (e.g., Tableau, Power BI) to create effective dashboards for KPI reporting.