Data Scientist

at  Nedbank

ESSENTIAL QUALIFICATIONS - NQF LEVEL

• Matric / Grade 12 / National Senior Certificate
• Advanced Diplomas/National 1st Degrees

PREFERRED QUALIFICATION

• STEM Qualification
• Engineering Qualification,
• Computer Science,
• Econometrics,
• Mathematical Statistics,
• Actuary Science
• Masters or Doctorate will be an added advantage

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

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.