Please Note: Preference will be given to applicants from Underrepresented Groups
Job Family
Information Technology
Career Stream
Application Development
Leadership Pipeline
Manage Self Expert (MSE)
FAIS Affected
Job Purpose
Lead in designing and building next-generation analytic engines and services, applying substantial expertise in machine learning, data mining, and information retrieval to drive impactful solutions and contribute to data-driven decision-making
Job Responsibilities
Development of statistical models and algorithms
Conduct statistical analysis to gain insights from complex datasets, supporting data-driven decision-making efforts.
Offer insights and observations to stakeholders, identify trends and measure performance
Support the creation of value from data, assisting in translating data into meaningful business solutions.
Gain proficiency in financial services domain concepts and regulations to support the development of statistical models and AI/ML solutions tailored for financial applications.
Collaborate with experienced banking professionals to design and implement ML models that meet the unique requirements of financial institutions.
Contribute to shaping the organization's AI/ML strategy with the support of senior team members.
Participate in converting data science prototypes into scalable machine learning solutions for potential deployment.
Support the design of ML models and systems, considering adaptability and retraining capabilities under the guidance of experienced team members.
Participate in the assessment of ML system performance to ensure alignment with corporate and IT strategies, collaborating with experienced colleagues.
Job Responsibilities Continue
Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture.
Strong proficiency in programming tools (such as Python, R, etc) for data manipulation, statistical analysis, and machine learning tasks is essential.
Familiarity with big data frameworks, such as Apache Hadoop or Spark, and have a willingness to learn and grow their expertise in handling and analyzing large-scale datasets
Utilize machine learning algorithms and libraries with hands-on experience.
Support software engineering and design aspects of projects with mentorship from cross-functional teams.
Contribute to end-to-end designs with support from experienced team members.
Adapt communication for non-programming experts.
Stay informed about the latest tools and techniques, engaging in continuous learning.
Contribute to the evaluation of data distribution variations impacting model performance.
Apply foundational analytical techniques to support business value through ML and AI.
Familiarity with cloud computing concepts and basic experience in deploying data science solutions on cloud platforms
Collaborate with the team, sharing ideas and insights.
Assist in the development of ML roadmaps.
Seek learning opportunities and contribute to knowledge-sharing within the team.
Contribute to the achievement of the business strategy, objectives, and values as a valuable team member.
STEM Qualification
Engineering Qualification,
Computer Science,
Econometrics,
Mathematical Statistics,
Actuary Science
Masters or Doctorate will be an added advantage
Essential Certifications
Preferred Certifications
Minimum Experience Level MS/PhD in STEM or related technical discipline
3-7 years' experience in a statistical and/or data science role
Deep knowledge of machine learning, statistics, optimization, or related field
Experience with R, Python, Matlab is required, programming in C, C++, Java
Experience working with large data sets, simulation/ optimization, and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
Excellent written and verbal communication skills along with strong desire to work in cross functional teams
Attitude to thrive in a fun, fast-paced start-up like environment
Technical / Professional Knowledge
Data Mining
Research and analytics
Data Tools
Data analysis
Statistical Analysis
data/ data structures
Presentation Skills
Problem solving skills
Supervised Learning
Unsupervised Learning
NLP
Deep Learning
Feature Engineering/Selection
HyperParameter Tuning
programming
Model Deployment/Monitoring
Big Data Technologies
Data Integration/Pipelines
Data Modelling
Data Visualisation
Domain Knowledge
AI Ethics and Fairness
Behavioural Competencies Decision Making
Innovation
Technical/Professional Knowledge and Skills
Customer Focus
Applied Learning
Continuous Improvement
- Please contact the Nedbank Recruiting Team at +27 860 555 566
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