Data Scientist, Gen AI at Safaricom Kenya

JOB DESCRIPTION

• 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.

QUALIFICATIONS

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