Lead Data Scientist

Responsibilities

1. Strategy. Coordinate and manage organization-wide efforts to harness the power of data across the institution. The Lead Data Scientist will lead on:

• Vision & Strategy: Consolidate existing efforts and approaches into a vision and strategy for using data across the institution and how separate programs can appropriately share data for collective analysis and use;
• Roadmaps: Develop and implement both strategic and tactical data management roadmaps in coordination with other technical staff and organizational stakeholders;
• Data Handling: Engage with Corporate IT to employ high performance computing and software engineering to fully unlock the use of statistical models and machine learning on the combined wealth of data assets in the company;
• Strategic partnering: Lead the organization’s engagement with stakeholders that can enhance and accelerate the data science practice in JSI;
• Data Use Agreements: Engage with project teams on drafting data use agreements;
• Good Governance: Advise on sound governance processes and approaches with regard to sensitive data;
• Innovation: Drive enterprise-wide data transformation through innovation approaches to collect, manage, and analyze data to improve health and education outcomes;
• Ethics: Ensure that data science activities are conducted with full awareness of the ethical, policy, privacy, security, and equity considerations; and
• Communications: Consolidate existing operational procedures into standards-based guidance on exploring, analyzing, and visualizing data in a way that effectively communicates results and findings.

2. Technical Leadership and Assistance. The Lead Data Scientist will provide technical leadership and assistance with all aspects of data across the institution. The person will:

• Data Strategy: Provide data strategy support to programs and countries including identifying current and anticipated future data needs, identifying the data ecosystem and the supporting enterprise architecture;
• Requirement Gathering: Provide data and analytics requirements as input to all technology planning activities with input from the leadership and other business teams;
• Operationalize Data: Enable the wrangling and transformation of data in order to perform meaningful analyses, data usability, availability, and quality through a range of tools and approaches as well as supporting a strong organizational approach to data management;
• Analytics: Support data analytics through machine learning, statistical modeling, and other advanced analytics methods and reporting on how the data provides insights towards improved health and education outcomes;
• Leverage New Tools: Capitalize on innovative technologies such as Artificial Intelligence (AI) to apply methods for big data to reveal patterns, trends, and associations;
• Information Sharing: Support the development, documentation, and dissemination of data-driven lessons learned;
• Programming, Tools, and Platforms: Support data science approaches to consider big data needs and practices by advising on appropriate coding, visualization, database, and software platforms; and
• Solution Oriented: Identify and propose existing enterprise data challenges, identify root cause, and propose a resolution.

3. Other duties and Responsibilities. As a technical leader in the institution, leverage your skills with a variety of teams across the organization to support the following:

• Mentorship and Supervision: Provide direction, guidance, and mentorship to data-driven individuals across the organization and supervise relevant staff such as the AI Advisor;
• Training: Provide training sessions (aka Learning Labs) to enlighten colleagues on technical approaches to using data as a development tool;
• Be a Champion: Champion data literacy, data consistency, and support for data initiatives within the organization; and
• NBD: Support new business development initiatives as technical lead or technical inputter (depending on organizational needs) with creative solutions that can be incorporated into proposals.

Skillset

• Bachelor’s degree in IT, Data Science, Computer Science, Software Engineering, Information Systems, Health Informatics, Biostatistics or related field. An advanced data science, computer science, public health, education, or statistics degree is a distinct advantage.
• 10 plus years’ experience in a complex and fast-paced setting with at least 5 years working as a data lead.
• Strong technical skills and knowledge of applications and technologies such as R, Python, HTML, PostgreSQL, PowerBI, Tableau, ArcGIS, SPSS, and Stata.
• Excellent business acumen and interpersonal skills in order to work across departmental lines at senior levels to effect change and achieve common goals.
• At least 5 years of progressive experience leading cross-functional teams and enterprise-wide initiatives.
• A proven track record of developing, implementing, and documenting an enterprise data strategy and participating in the development of an enterprise architecture to support it.
• Demonstrable skills in applying monitoring and evaluation concepts for inventorying, and cataloging in enterprise or national level data platforms for large multidimensional datasets.
• Ability to apply data science principles and methods to track changes and objectively measure progress towards the achievement of enterprise-wide or national targets, and to communicate the data.
• Strong project management and time management skills; highly organized and detail-oriented.
• Previous work experience with USAID-funded projects and/or international development organizations.
• Experience working in low-and-middle-income countries within health or development is a plus.
• Proven ability to manage the development and implementation of project activities.
• Strong representational and interpersonal skills.
• Excellent written and verbal English; French proficiency preferred. A history of technical and peer-reviewed academic publications advancing data science is a plus.
• Ability to prepare and present technical information to staff around the world, partners, and donors.
• Ability to work in a dynamic team-oriented environment but self-managing of own time.
• Ability to work independently, take responsibility, and follow through on assignments.
• Ability to travel domestically and internationally +/- 15%.
• A sense of humor and the ability to bring joy to the work environment.