Data Scientist at Nedbank

Job Purpose

Lead the design, development, and implementation of cutting-edge analytic engines and services, leveraging extensive experience and expertise in machine learning, data mining, and information retrieval to pioneer innovations.

Job Responsibilities

• Spearheaded best-in-class statistical models and algorithms, building upon previous experiences and learnings.
• Conduct in-depth statistical analysis to extract valuable insights and patterns from complex datasets, contributing to data-driven decision-making.
• Offer actionable insights and advice to stakeholders, utilizing a solid foundation in AI/ML and contributing to the team's expertise.
• Contribute to the creation of value from enterprise-wide data, assisting in the translation of data into meaningful business solutions.
• Apply specific financial services domain knowledge to analyse datasets and develop statistical models and algorithms that cater to individual financial services use cases.
• Design and implement ML models with experienced banking professionals that meet the unique requirements of financial institutions.
• Implementation of cutting-edge AI and ML solutions, playing an active role in system operations and maintenance.
• Experienced in deploying or contributed to deployment of at least one end to end data science solutions that has yielded significant value in the organisation at an enterprise level.
• Contribute to the shaping of the organization's AI/ML strategy, aligning it with evolving business needs.
• Assist in transforming data science prototypes into scalable machine learning solutions for deployment.
• Collaborate with experienced team members to design dynamic ML models and systems, incorporating the capability for adaptability and retraining.
• Participate in periodic evaluations of ML systems, ensuring they align with corporate and IT strategies.
• Expert proficiency in programming tools (such as Python, R, etc) for data manipulation, statistical analysis, and machine learning tasks is essential.
• Demonstrate a profound command over computer science fundamentals, encompassing expert-level knowledge of data structures, algorithms, computability and complexity, and computer architecture.
• Demonstrate a strong understanding of applications and machine learning algorithms, aligned to best practices globally.
• Spearheading and guiding the software engineering and design facets of projects, while providing mentorship and fostering collaboration among cross-functional teams.
• Utilize machine learning algorithms and libraries effectively, following established best practices and guidelines.
• Communicate technical concepts effectively to diverse audiences, adapting explanations for non-programming experts.
• Stay informed about the latest tools and techniques, engaging in continuous learning to enhance skills and knowledge.
• Able to the evaluate data distribution variations impacting model performance.
• Proficiency in cloud computing and hands-on experience with deploying complex data science projects on cloud platforms
• Collaborate with the team, sharing ideas and insights while conducting experiments and researching best practices.
• Leading role in formulating and refining the Machine Learning (ML) roadmaps or a component thereof, drawing upon extensive experience and visionary insights.
• Has a deep understanding of business problems and can design complete analytics solutions end to end
• Seek opportunities for personal growth and development, actively participating in knowledge-sharing and mentorship.
• Contribute to the achievement of the business strategy, objectives, and values, contributing to the organization's success.
• Participate in establishing a positive team culture and contribute to corporate responsibility initiatives.
• Contribute to the establishment of the Nedbank culture and participate in corporate responsibility initiatives to align with business strategy.

Job Responsibilities Continue

• Lead and develop Data Science Use Cases with a small team in an agile.
• Machine learning and Model training/retraining and development.
• Exploratory data analysis and visualizations using large data sets.
• Acquire and load relevant data and generate features from this data sets.
• Implement and integrate models into production systems.
• Exposure/Experience
• ML Engineering
• Data warehousing
• Advance analytics 
• Predictive analytics
• Data mining

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
• Preferred Certifications
• Cloud (Azure, AWS), DEVOPS or Data engineering certification. Any Data Science certification will be an added advantage, Coursera, Udemy, SAS Data Scientist certification, Microsoft Data Scientist.

Minimum Experience Level

• 5 years’ plus  experience in a statistical and/or data science role.
• 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      
• Deep knowledge of machine learning, statistics, optimization or related field
• Experience in Python (Must), R and one additional language (SAS, Java Lua, Clojure, Scala, etc)
• Experience in end to end Data Science Use cases