We are looking for a seasoned data analyst to be responsible for coordinating and leading the implementation of our data strategy and standards across the business, including:
Implementation of a common data model and taxonomy.
Ensuring continuous integrity of data assets.
Leveraging data assets into actionable insights.
QUALIFICATIONS
A degree in computer science, data science, operations research, statistics, applied mathematics, or a related quantitative field. Equivalent work experience in areas such as finance, supply chain management, engineering, and manufacturing operations is a plus. Experience in more than one area is strongly preferred.
EXPERIENCE
At least five years of relevant project experience in successfully executing data science projects.
Project experience should include the application of data science techniques and technologies (including machine learning) to business functions such as financial analytics, manufacturing, sales and distribution, transportation, customer journey analytics, marketing analytics, e-commerce platform, process control, and others.
MINIMUM SKILLS AND ABILITIES REQUIRED
IT knowledge/skills
Experience with popular database programming languages including SQL, PL/SQL, and others for relational databases.
Experience with nonrelational databases (such as NoSQL/Hadoop-oriented databases) and distributed data/computing tools such as Hadoop/MapReduce, Hive, Kafka is a plus.
Basic to substantial knowledge of relevant coding languages and tools: for example, Python/Jupyter, Java, Scala, Excel, MATLAB is a plus.
Experience of working across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems, and through containerization techniques such as Kubernetes and others.
Machine learning and data science knowledge/skills
Knowledge and experience in statistical and data mining techniques (such as generalized linear model/regression, hierarchical clustering, deep learning, neural network models, stochastic and graph analysis, and others).
Basic expertise in solving visual and text analytics, scoring, failure prediction, and associated problems is a plus. Basic knowledge of data discovery/analysis platforms (for example Microsoft Azure ML, Google Cloud ML, and others).
Interpersonal skills and characteristics
Must demonstrate the ability to work in diverse, cross-functional teams, in a dynamic business environment. Must demonstrate the ability to respond effectively to changing environments (expected and unexpected). Ability to evolve own ideas and solutions in response to changing circumstances.
Demonstrate the ability to use different problem-solving approaches and select the one that best meets the requirements of the situation. Keep the big picture of the problem in mind while focusing on its specifics.
Must have excellent communication skills, both written and verbal. Demonstrate the ability to effectively interpret the needs of all stakeholders, respond to their needs, and manage expectations.
Ability to collaborate with all stakeholders in the pursuit of common goals. Must have strong interpersonal skills to work with and influence large teams.
Must be self-driven, curious, and creative. Focus on desired results and business outcomes. Define performance standards in terms of doing what is appropriate (and doing it well). Work to achieve goals despite barriers or difficulties.
ROLES AND RESPONSIBILITIES
As a Data Analyst for Restonic, your functions will be as follows:
Problem Analysis and Project Management
Collaborate across the business to understand IT and business constraints. (Help to) identify data-driven business opportunities. Manage data science projects and the corresponding key performance indicators (KPIs) for success. (Help to) communicate data management and governance principles.
Data Collection and Integration
Understand existing data sources and process pipelines, and document them appropriately. Ensure data pipeline integrity and alignment to company standards. (Help to) improve existing (and create new) data pipelines for more efficient and repeatable analytics/decision support solutions, in line with prioritized business objectives.
Data Exploration and Preparation
Network with subject matter experts (process owners) to better understand the business mechanics that generate the data assets. Apply statistical analysis and visualization techniques to various data elements. Generate hypotheses about the underlying mechanics of the business processes. Test hypotheses using various (appropriate) quantitative methods.
Operationalization
Apply machine learning (ML) and other advanced analytics techniques to perform classification and/or prediction tasks.
Work with subject matter experts to integrate domain knowledge into the analytics solution.
Implement appropriate testing of analytics models, such as cross-validation, bias, fairness, and others.
Collaborate with solution vendors, data engineers, and IT to evaluate and implement analytics/ML deployment options.
(Help to) establish best practices around analytics/ML technical infrastructure and continuously monitor execution and health of the models.
Other (interpersonal and organizational)
Train other business and IT staff on basic data science principles and techniques.
Network effectively with internal and external partners/stakeholders.
Promote collaboration with other data analysts and teams within the group (in line with the digital execution framework). Encourage re-use of models/artifacts.
Continuously develop own skills (through conferences, publications, courses, academia, and meetups).
Job Type: Full-time
Pay: R60000,00 - R75000,00 per month
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