Data Scientist at Nedbank

Job Purpose
To design, prototype, and build next-generation analytic engines and services by applying strong expertise in maching learning , data mining and information retrieval

Job Responsibilities

• Develop best-in-class statistical models and algorithms
• Conducts advanced statistical analysis
• Provide actionable insights, identify trends, and measure performance
• Create value out of enterprise wide data
• Provide insights to BI and BA to further exploit and present their models
• Provide strategic direction ito data information received
• Apply advanced analytical techniques such as machine learning and artificial intelligence in order to derive business value.
• Conduct data discovery for inclusion in models.
• Collaborate with key stakeholders to obtain business acumen and intellectual property
• Keep abreast with latest tools and techniques
• Understands business problems and designs end-to-end analytics use cases
• Collaborates with model developers to implement and deploy scalable solutions
• Develop complex models and algorithms that drive innovation throughout the organization.
• Ensure improvement of on-time performance and network planning,
• Provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders.
• Work with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.).
• Ensure understaning of  pros and cons of different analytics approaches for problem type.
• Implements more advanced algorithms, e.g., complex descriptive.
• Ensure Quality controls of  own work and those of junior scientists.
• Understand current state of analytics more broadly and apply techniques from across industries.
• Map problems and quantify the impact of proposed measures.
• Develop and prioritise use case roadmaps
• Support the achievement of the  business strategy, objectives and values by reviewing Nedbank and Business Unit Plan and ensuring delivered systems, process, services and solutions are aligned.
• Improve personal capability and stay abreast of developments in field of expertise by identifying training courses and career progression for self through input and feedback from managers.
• Ensure personal growth and enable effectiveness in performance of roles and responsibilities by ensuring all learning activities are completed, experience practiced and certifications obtained and/or maintained within specified time frames.
• Enable skilling and required corrective action to take place by sharing knowledge and industry trends with team and stakeholders during formal and informal interaction.
• Obtain buy-in for developing new and/or enhanced processes (e.g. operational processes) that will improve the functioning of stakeholders' businesses by highlighting benefits in support of the implementation of recommendations.
• Support the achievement of the  business strategy, objectives and values
• Stay abreast of developments in field of expertise 
• Ensure personal growth and enable effectiveness in performance of roles and responsibilities  
• Contribute to the Nedbank Culture building initiatives (e.g. staff surveys etc.).
• Participate and support corporate responsibility initiatives for the achievement of business strategy
• Seek opportunities to improve business processes, models and systems though agile thinking. 

Essential Qualifications - NQF Level

• Professional Qualifications/Honour’s Degree

Preferred Qualification

• BSC Computer Science, BSc Engineering, Econometrics, Mathematical Statistics , Actuary Science or any Stem Qualification.

Preferred Certifications

• Machine Learning and Data engineer related

Type of Exposure

• ML Engineering
• Data warehousing
• Advance analytics
• Marketing analytics
• Financial analytics
• Presentations skills 
• Predictive analytics
• Data mining
• Strategy formulations 

Minimum Experience Level

• 5-7 years' experience in a statistical and/or data science role

Technical / Professional Knowledge

• 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 working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.)
• Experience in end to end Use case delivery
• Ability to translate data narrative to business narrative
• 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
• ML Ops (Cloud Devops) is an added advantage.
• ML Ops (ML engineering – running a Data Science platform) is an added advantage.

Behavioural Competencies

• Strong problem solving skills
• Good communication skills
• Ability to work in teams
• Decision Making
• Innovation
• Continuous Improvement