Senior Data Analyst

Experian

Bryanston, Johannesburg
Permanent
Full-time

1 month ago

Company DescriptionExperian plc is an Anglo-Irish multinational consumer credit reporting company.Experian collects and aggregates information on over 1 billion people and businesses, including 235 million individual US consumers and more than 25 million US businesses.We operate in 37 countries with offices in the United Kingdom, the United States and Brazil.We employ approximately 17,000 colleagues, and last fiscal year, our year-end revenue was US$5.18 billion.Our product proposition covers credit services, Decision Analytics and marketing assistance to businesses, including individual fingerprinting and targeting.Job DescriptionAn experienced Senior Data Analyst who will be responsible for processing, analysing, and interpreting large amounts of data to identify best practices, insights and patterns that will add value and improve our data platform and data offering. To support and manage client delivery and engagement and help us maintain our position as a market leader. The ideal candidate will have strong analytical and statistical expertise in T-SQL, Python and Azure, and possess critical thinking and problem-solving skills to support client delivery and day to day undertakings. They will also have a passion for machine learning and research, keeping abreast of the latest techniques and industry updates and be able to communicate and demonstrate their findings effectively to management and their team. The candidate will engage with other teams on data products and solutions and use their analytical and statistical expertise to transform complex data sets into actionable insights that drive business growth and success. They will perform thorough data validation and testing, to ensure that the data is properly cleansed, transformed, and stored. Implementing quality control measures to ensure data accuracy and reliability throughout the data lifecycle. Attention to detail and commitment to data quality will be critical to the success of the role.QualificationsBSc/BA in Computer Science math, software engineering, statistics, data science or a related technical field with 3 to 5 years of work experience. Microsoft SQL certification.Functional

Proven experience as a Data Scientist or

. * Experience in data warehousing, ETL processes, data mining and data modelling.

Experience with big data technologies (e.g., Hadoop, Spark).
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of Microsoft SQL Server, T-SQL, Azure and Python.
Proficiency in data visualization tools (e.g., Power BI, Tableau).
Analytical mind and business acumen.
Strong math skills (e.g., statistics, algorithms).
Problem-solving aptitude.
Excellent communication and presentation skills.
Ability to work independently and with team members from different backgrounds.
Excellent attention to detail.
A drive to learn and master new technologies and techniques.
Working with large datasets and moving of files between different environments.
Import and Export data from different database technologies.
Process automation and monitoring.
Code migration from legacy languages and systems.
Data Cleansing
Data profiling
Excellent team player and collaboration skills.
Ability to prioritize and manage multiple tasks and projects simultaneously.

TechnicalExperienced and knowledgeable in the use of tools and techniques such as

Microsoft SQL Server
T-SQL
Azure Data Platform Stack
Azure Data Lakes/Blob
Azure HDInsight (Apache Spark)
Azure Databricks
Python
Statistics

Additional InformationPrinciple responsibilities

Identify valuable data sources and automate collection, loading and transforming processes.
Developing and maintaining databases, data systems, and data pipelines.
Efficient Data Engineering (ETL).
Data investigations and anomaly detection in data.
Manage scheduled client and business processes and deliverables.
Undertake pre-processing of structured and unstructured data.
Analyse large amounts of information to discover trends and patterns.
Build predictive models and machine-learning algorithms.
Provide rapid feedback and insight on ad-hoc requests.
Present information using data visualization techniques.
Propose solutions and strategies to business challenges.
Collaborate with client and product development teams.
Undertaking data collection, pre-processing, and analysis.
Building models to address business problems.
Code migration from legacy languages.
Creating reports and presentations for business uses.
Correlating similar data to find actionable results.
Managing and administrating monthly business processes.
Client and business communication.

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