Responsibilities
Translate organizational needs into data, analytics
and reporting requirements to support decisions, strategies and workflows with
data and information.
Identify, analyze, and interpret trends or patterns,
using machine learning techniques, statistical methods to identify relevant
features and variables in structured and unstructured sources of information
and data.
Design, implement, and operate UNEP enterprise data
platforms, including the establishment of a data governance framework and the
development of data pipelines.
Oversee the full data analytics lifecycle, from
requirements and design to the building of analysis, reporting and quality
control capabilities.
Ensure technically sound execution of data analytics
projects.
Collaborate with colleagues across departments to
identify data analytics needs and support data-driven projects.
Translate immediate requirements into prototype
solutions and oversee their subsequent full implementation.
Keep track of trends and developments in data
analytics best practices, tools, etc.
Competencies
PROFESSIONALISM: Knowledge analytical skills with the ability to collect,
organize, manage, and disseminate significant amounts of information with
attention to detail and accuracy. The ability to analyze, model and interpret
data in support of decision-making. Adept at queries, report writing and
presenting findings. The ability to oversee and quality-check work completed by
other team members. Takes pride in the work for the organization and
understands the impact that can be brought into the organization by allowing
data-driven and evidence-based decisions. Ability to apply judgment in the
context of assignments given, plan own work and manage conflicting priorities.
Shows pride in work and in achievements; demonstrates professional competence
and is conscientious and efficient in meeting commitments, observing deadlines
and achieving results; is motivated by professional rather than personal
concerns; shows persistence when faced with difficult problems or challenges;
remains calm in stressful situations. Takes responsibility for incorporating
gender perspectives and ensuring the equal participation of women and men in
all areas of work.
TEAMWORK:
Works collaboratively with colleagues to achieve organizational goals; solicits
input by genuinely valuing others’ ideas and expertise; is willing to learn
from others; places team agenda before personal agenda; supports and acts in
accordance with final group decision, even when such decisions may not entirely
reflect own position; shares credit for team accomplishments and accepts joint
responsibility for team shortcomings.
PLANNING AND ORGANIZING: Develops clear goals that are consistent with
agreed strategies; identifies priority activities and assignments; adjusts
priorities as required; allocates appropriate amount of time and resources for
completing work; foresees risks and allows for contingencies when planning;
monitors and adjusts plans and actions as necessary; uses time efficiently.
CLIENT ORIENTATION: Considers all those to whom services are provided to be
“clients” and seeks to see things from clients’ point of view; establishes and
maintains productive partnerships with clients by gaining their trust and
respect; identifies clients’ needs and matches them to appropriate solutions;
monitors ongoing developments inside and outside the clients’ environment to
keep informed and anticipate problems; keeps clients informed of progress or
setbacks in projects; meets timeline for delivery of products or services to
client.
Education
Advanced university degree (Master’s degree or
equivalent) in computer science, data science, analytics, engineering,
statistics, or a related field is required.
A first level university degree in combination with
two (2) additional years of relevant qualifying experience may be accepted in
lieu of the advanced university degree.
Work Experience
A minimum of seven (7) years of progressively
responsible experience in applied analytics, data science, business
intelligence, statistics, project management, or related area is required.
Experience in developing digital solutions using
data, artificial intelligence and machine learning techniques to advance
decisions, strategies and execution is required.
Experience in designing data integration and pipeline
architectures which must include ingesting data through different methods such
as message queues, database connections, files, or Application Programming
Interface (APIs), is required. Experience with self-service analytics and data
visualization applications (MS PowerBI, Qlik, Tableau or similar), or business
intelligence tools (SAP Business Objects, etc.) is desirable.
Experience in DevOps tools chains consisting of tools
like Git, Jenkins, Bamboo or equivalent is desirable.
Experience with data science tools and programming
languages (SQL, Python, R) is desirable.
Experience in delivering big data use cases is
desirable, including projects using technology such as Apache Spark, Hadoop or
others.
How To Apply