Talent Resources

A role for driving business value with data 

Data Analysts can interrogate databases, extract relevant data, and carry out descriptive analysis using a range of BI tools. More importantly, they can transform data into insights and make commercially profitable recommendations that drive business value.    

Responsibilities 

Our talented Data Analysts will be able to: 

• Identify, evaluate and implement external services and tools to support data validation and cleansing 
• Liaise with internal and external clients to fully understand data content 

• Gather, understand and document detailed business require-ments using appropriate tools and techniques 
• Manipulate, analyse and interpret complex data sets relating to the employer’s business 
• Prepare reports for internal and external audiences using BI reporting tools 
• Create data dashboards, graphs and visualisations 
• Provide sector and competitor benchmarking 

• Mine and analyse large datasets, draw valid inferences and present them to management using a reporting tool. 

What Our Candidates Offer: 

Skills: 

• Excellent numerical and analytical skills 
• Experience of data analysis and visualisation tools  
• Familiarity with prevalent relational databases 
• Experience of data modelling, data cleansing, and data enrichment techniques 
• Hadoop open-source data analytics 

• The capacity to develop and document procedures and workflows 
• The ability to carry out data quality control, validation and linkage 
• An understanding of data protection issues 
• Experience of statistical methodologies and data analysis techniques 
• The ability to produce clear graphical representations and data visualisations 

Technologies and Tools: 

• VBA and SQL Server 
• BI and analytics platforms – MS Power BI, Tableau, QlikView 
• Statistical programmes – SPSS, SAS 

• Programming for data and analytics – R, Python 
• APIs 
• XML 

A role at the heart of business transformation 

Data Scientists can extract, analyse and interpret large amounts of data from a range of sources, using algorithmic, data mining, artificial intelligence, machine learning and statistical tools, to help businesses solve problems in innovative ways. 

Responsibilities 

Our talented Data Scientists will be able to: 

• Work closely with your business to identify issues and use data to propose solutions for effective decision making 
• Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation 
• Use machine learning tools and statistical techniques to produce solutions to problems 

• Test data mining models to select the most appropriate ones for use on a project 
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results 
• Create clear reports that tell compelling stories about how customers or clients work with the business 
• Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods 

What Our Candidates Offer: 

Skills: 

• Excellent analytical and problem-solving skills 
• Deep knowledge of Big Data architecture with Hadoop Cluster 

• Advanced T-SQL queries to manipulate large and complex data sets 
• Advanced statistical modelling and machine learning algorithms for advanced statistical analysis, regression, econometrics, random forests, SEM, decision trees, and so on. 
• Advanced knowledge of deep learning, NLP, NLG, and so on. 
• Advanced predictive modelling for Business Analytics use cases (for churn, acquisition, campaign analytics, customer journey, fraud detection, risk, pricing, complaints reduction and low NPS prevention) 
• Business Intelligence – Building operational dashboards including data migration, warehousing, architecture modelling and dashboard reporting 

• Exceptional communication and presentation skills  

Technologies and Tools: 

• Programming for data and analytics – R, Python 
• Framework – TensorFlow 

• Statistical programmes – SPSS, SAS 
• BI and analytics platforms – MS Power BI, Tableau, QlikView 
• VBA and SQL Server 
• APIs 
• XML 

The top emerging job in 2020 

AI Engineers can build, test, and deploy AI models, as well as maintain the underlying AI infrastructure. They are problem-solvers who can navigate between traditional software development and machine learning implementation. 

Responsibilities 

Our talented AI Engineers will be able to: 

• Coordinate between Data Scientists and Business Analysts 
• Automate infrastructure used by the Data Science team 

• Convert machine learning models into APIs so that other applications can access them 
• Test and deploy models 
• Develop minimum viable products based on machine learning 
• Automate processes by utilizing machine learning 
• Use AI to empower the company with novel capabilities 

What Our Candidates Offer: 

Skills: 

• Knowledge of linear algebra, probability, and statistics 

• Knowledge of Spark and other Big Data technologies 
• Knowledge of programming languages to build and implement models 
• Understanding of machine learning algorithms, such as linear regression, KNN, Naive Bayes, Support Vector Machine, and others to implement machine learning models 
• Understanding of deep learning algorithms, such as a convolutional neural network, recurrent neural network, and generative adversarial network 
• Knowledge and experience of using AI technologies, such as NLG, text analytics and NLP, speech recognition, image recognition, virtual agents, and so on. 

• Ability to implement machine learning models using a framework 
• Excellent communication and problem-solving skills 

Technologies and Tools: 

• Machine learning platforms 

• Deep learning platforms 
• Programming languages – Python, R, Java, and C++ 
• Big Data technologies – Hadoop, Cassandra, and MongoDB 
• Frameworks – PyTorch, Theano, TensorFlow, and Caffe 

A role for driving business value with data 

BI Developers are in charge of developing, deploying, and maintaining BI interfaces. Those include query tools, data visualisation and interactive dashboards, ad hoc reporting, and data modeling tools.  

Responsibilities 

Our talented Cloud BI Developers will be able to: 

• Aggregate data from multiple sources in an efficient data warehouse and design enterprise-level solutions for very large multidimensional databases 
• Design, build and deploy BI solutions (e.g. reporting tools) 
• Maintain and support data analytics platforms 
• Debug, monitor and troubleshoot BI solutions 

• Collaborate with teams to integrate systems 
• Develop and execute database queries and conduct analyses 
• Create visualisations and reports for requested projects. 

What Our Candidates Offer: 

Skills: 

• Understanding of all the underlying infrastructure, including data integration tools, ETL/ELT processes, data formatting, and warehouse architecture 
• Experience of dealing with databases 
• Understanding of business requirements for BI systems 

• Python knowledge and scripting languages 
• Experience with data visualisation libraries 
• Software engineering skills 
• Strong troubleshooting skills 

Technologies and Tools: 

• Cloud Platforms, ETL, Microsoft SSIS, SSAS, SSRS, Power BI, SAP, and so on. 

Instrumental in rolling out analytics applications 

Big Data Engineers facilitate getting data from a variety of different sources, getting it in the right formats, assuring that it adheres to data quality standards, and assuring that downstream users can get that data quickly, so they can perform whatever downstream task that is, whether reporting or exploratory analytics or building a new model or an algorithm. 

Responsibilities 

Our talented Big Data Engineers will be able to: 

• Create and maintain optimal data pipeline architecture. 
• Assemble large, complex data sets that meet functional/non-functional business requirements. 
• Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, redesigning infrastructure for greater scalability, etc. 
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using ‘big data’ technologies. 
• Build analytics tools that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. 

• Work with data and analytics experts to strive for greater functionality in their data systems. 

What Our Candidates Offer: 

Skills:

• Knowledge of Big Data frameworks or Hadoop-based technologies. Mastering Big Data tools, such as HDFS, YARN, MapReduce, PIG and HIVE, and so on. 
• Knowledge of real-time processing framework – Apache Spark 
• Understanding of database design and database architecture, Data Models and Data Schema 
• Knowledge of SQL-based technologies 
• Knowledge of NoSQL technologies – Cassandra and MongoDB 

• Knowledge of a programming language, such as Python or R 
• Knowledge of ETL and data warehousing solutions 
• Understanding Industry-wide various operating systems, such as UNIX, Linux, Solaris or MS Windows 
• Understanding of complete data flow and business model