Job Title: Data Scientist, Gen AI Job Safaricom
Hiring Organization: Safaricom PLC
Location – Locality: Nairobi
Location – Region: Kenya
Industry: Telecommunication
Job Type: Full Time
Salary: KES
Date Posted: 05/29/2024
We are
pleased to announce the Data Scientist, Gen AI vacancy in the AI tribe. In
keeping with our current business needs, we are looking for a person who meets
the criteria indicated below.
Brief
Posting Description
The role
holder will be responsible for building scalable AI systems and contribute to
the democratization of AI across Safaricom. They will deliver the use-cases
identified, while also building data science capacity within organization and
business clusters they support.
The ideal
candidate will be well versed with building AI systems especially GenAI.
Responsibilities
Below are
the key skills and competencies required to be successful in this role:
Automated
AI Modelling:
Ability
to creatively solve business problems by building AI systems.
Ability
to Constructively disrupt current business practices using Generative AI
(GenAI).
Designing
and developing scaled (Gen)AI solutions.
Show a
propensity to collaboratively work with the larger team in the AI tribe to
productionize AI algorithms.
Being
able & willing to stretch yourself to work on other multiple data science
projects.
Ability
to test hypotheses from raw data sets, draw meaningful conclusions, and
effectively communicate results verbally, in writing, and through effective
visualization
Quantify
improvements in business areas resulting from the use of algorithms and
modelling through A/B testing
Statistical
& ML Modelling:
Demonstrate
competency in utilizing advanced statistical and machine learning methods and
technologies to deliver best-in-class models to support risk decision making.
Developing
code and automated processes to manipulate high volume, high dimensional data
sources, including alternative data, to extract informative patterns, perform
exploratory analyses and engineer useful features.
Ability
to develop machine learning & deployment of models and algorithms from
large volumes of structured and/or unstructured data in a commercial /consumer
environment in order solve real business problems, taking account of user needs
and technology and operational landscape
Identifying
new analytics trends and opportunities to drive the innovation agenda across
business functions
Programming
Languages and Big Data Technologies:
Along
with a strong knowledge of Big Data Technologies, the candidate should have:
Practical
skills in GIT version control.
Strong
hands-on programming skills in Python. Knowledge of SQL, Hadoop/Hive, Spark,
and/or Scala.
Proficient
in AI libraries in Python (e.g. H2O, SciPy and NLTK, PyTorch etc.)
Familiar
with leading visualisation tools (e.g. Tableau, Qliksense, QuickSight)
Cloud
computing, especially AWS
Behavioural
Competencies:
Ability
to work cross functional teams to translate business issues into potential
analytics solutions
Excellent
communication skills with the ability to document solutions effectively.
An
analytical mindset to identify patterns and insights from data and business
processes.
The
ability to collaborate with cross-functional teams to assess business needs and
develop AI solutions.
A
self-driven and creative mindset to apply AI methods to solve real issues.
Ability
to provide effective leadership and guidance to junior data scientists
A
problem-solving aptitude.
Experience
& Education you should possess:
A degree
in Statistics, Mathematics, Data Science, Computer Science, or a related field.
An MSc in
a data science related discipline like Mathematics, Statistics, Computer
Scientist or Engineering will be an added advantage.
5+ years
of experience relevant to this role
Proven
work experience in advanced Gen (AI) techniques, including prompt engineering,
LLM implementation, and agent development, with a fundamental knowledge of
inner workings.
Experience
in cloud technologies, generative AI techniques, will be an added advantage.
Significant
experience in machine learning & deployment of models and algorithms from
large volumes of structured and/or unstructured data in a commercial /consumer
environment
