Jobs at Equity Bank Kenya

Job Purpose:   

1. Reporting to Head Data Science, the Data Engineer will be responsible for ensuring  proper execution of their duties and aide in building the organizations data collection systems and processing pipelines.  Provide oversights and expertise to Data Engineering practice that is responsible for the design, deployment, and maintenance of the business’s data platforms and pipelines.
2. The role holder will support the infrastructure, tools and frameworks   used to support the delivery of end-to-end solutions to business problems through high performing data infrastructure.
3. S/He will be responsible for expanding and optimizing the organizations data and data pipeline architecture, whilst optimizing data flow and collection to ultimately support data initiatives.

Job Responsibilities/ Accountabilities:

1. Support data analyst, data scientist and Senior data engineers, ensuring  proper execution of their duties and alignment with the Company objectives.
2. Provide Data Engineering expertise and responsible for the design, deployment, and maintenance of the business’s data platforms. Required to draw performance reports and strategic proposals form his gathered knowledge and analyses results for senior members of the data science team.
3. Own and extend the business’s data pipeline through the collection, storage, processing, and transformation of large data- sets and oversee the process for creating and maintaining optimal data pipeline architecture and creating databases optimized for performance, implementing schema changes, and maintaining data  architecture standards across the required databases.
4. Oversee the assembly of large, complex data sets that meet functional / non-functional business requirements and align data architecture with business requirements.
5. Oversee, design, and develop algorithms for real-time data processing within the business and to create the frameworks that  enable quick and efficient data acquisition. Deploy sophisticated analytics programs, machine learning and statistical methods.
6. Build analytics tools that utilise the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
7. Extract data from source systems using querying languages such as SQL and provide to data science team members
8. Develop and maintain data pipelines and applications
9. Create data tools for analytics and data scientist team members that assist them in building and optimising into an innovative industry leader.
10. Monitor the existing metrics, analyse data, and lead partnership with other Data and Analytics teams in an effort to identify and implement system and process improvements.
11. Utilise data to discover tasks that can be automated and identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
12. Acts as a subject matter expert from a data perspective and provides input into all decisions relating to data engineering and the use thereof. Provide guidance in terms of setting governance standards.
13. Ensure proper data governance and quality across all developments

Qualifications and Experience

1. Bachelors degree in Statistics,Software Engineering, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field.
2. 3 to 5 years experience in Technology handling data monetization; Including; big data tools: Hadoop, Spark, Kafka, relational SQL and NoSQL databases, including Postgres and Cassandra.
3. Experience with data     pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
4. Experience with stream-processing systems: Storm, Spark- Streaming, etc. Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
5. Ability to wrap Machine learning models around API
6. Knowledge of Software engineering
7. The candidate must also have a proven and successful experience track record of leading high-performing data analyst teams leading through the successful performance of advanced quantitative analyses and statistical modeling that positively impact business performance.
8. Strong analytic skills related to working with                 unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets.
9. Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
10. Ms Office/Software:  Outstanding skills in the use of Ms Word, Ms Excel, PowerPoint, and Outlook, which will all be necessary for the creation of both visually and verbally engaging reports and presentations, for senior data science management, executives, and stakeholders.
11. The candidate must also demonstrate exceptionally good skills in SQL server reporting services, analysis services, PowerBI, integration services, Salesforce, or any other data visualization tools.
12. Technological Savvy/Analytical Skills:  Technologically adept and especially demonstrate an understanding of database and computer software.
13. Must also be highly skilled in statistical and modeling packages such as SAS, Statistica, Matlab, R, visualization and other advanced analysis tools. He will also be an expert in data management programming such as SQL, PL-SQL, and Python as well as being familiar win the workings of motion-tracking data and time-series analyses.
14. Interpersonal Skills: A suitable candidate for this position will be a team-builder, be result-oriented, be proactive and self-driven requiring minimal supervision, be open and welcoming to change, be a creative and strategic thinker, have innovative problem-solving skills, be highly organized, have an ability to handle multiple simultaneous tasks prioritize and meet tight deadlines, and demonstrate calmness in times of uncertainty and stress.
15. People Skills:  a people person who is able to form strong, lasting, and meaningful bonds with others people. This will make him an approachable and trustworthy individual who junior personnel readily follow and who senior Data and Analytics executives and stakeholders trust and who’s insights they give credit to, making execution of his duties much easier.

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Job Purpose:   

1. Reporting to Head Data Science, the Senior BI developer will be responsible for the design, development and maintenance of new BI reports and dashboards using Power BI and other visualization tools. The employee will be working closely with data analysts, data scientists and data engineers on various projects including designing reports and dashboards that fulfil user needs.
2. The role holder will be highly organised, pro-activity, and enthusiastic towards assigned projects.
3. S/He will be responsible for leading a group of data analyst within the team towards the delivery of agreed business intelligence solutions.

Responsibilities of the Senior BI developer

1. Engage internal stakeholders to translate business requirements into technical requirements
2. Engaes external stakeholders such as Microsoft to conduct trainings and facilitate the resolution of niche BI development issues
3. Ensure positive stakeholder engagements throughout the lifecycle of a task or project
4. Lead data analyst and oversee their developments works ensuring the data presented is accurate, meets visualization best practices and is aesthetically pleasing to the eye
5. Develop and maintain BI applications and dashboards
6. Manage administration of business intelligence (BI) tools such as Power BI, Tableau etc
7. Support data analyst, data scientist and data engineers, ensuring  proper execution of their duties and alignment with the Company objectives.
8. Provide BI expertise and responsible for the design, deployment, and maintenance of the business intelligence solutions.
9. Create mockups, prototypes and develop visualization requirements by working with business teams & users
10. Work with the Data warehouse platform development team to understand the reporting sources to facilitate real-time reporting to operate in both analytical and operational capacities
11. Work with visualizing structured and unstructured data sets
12. Scale developments of BI solutions to other countries
13. Manage and support migration of objects (dimensions, measures, hierarchies, reports, workbooks, dashboards, scorecards, savings & utilization, etc) from development to production environments
14. Develop and format stored procedures in T-SQL
15. Communicate with non-technical employees to define report request and limitations
16. Ensure proper data governance and quality across all developments

 
Qualifications and Experience

1. Bachelors degree in Statistics, Software Engineering, Engineering, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field.
2. 5-7 years experience in BI developments with a preference for the finance industry
3. Should have excellent hands-on development experience with Power BI, and Microsoft tools such as word, power point and excel
4. Should have advanced level SQL/TSQL experience and able to implement the business logic through stored procedures.
5. Skilled in handling multiple deadline driven assignments with the ability to initiate, supervise and complete projects and assignments with minimal supervision
6. A broad exposure to various Business Intelligence platforms. Position requires excellent technical and communication skills. The ability to manage multiple projects/tasks simultaneously is a requirement of this position. Very detailed oriented.
7. Willingness to learn, be open minded to new ideas and different opinions yet knowing when to stop, analyze, and reach a decision
8. Some basic knowledge of data science and data engineering is preferred
9. The candidate must also have a proven and successful experience track record of leading high-performing data analyst teams
10. Ms Office/Software:  Outstanding skills in the use of Ms Word, Ms Excel, PowerPoint, and Outlook, which will all be necessary for the creation of both visually and verbally engaging reports and presentations, for senior data science management, executives, and stakeholders.
11. The candidate must also demonstrate exceptionally good skills in SQL server reporting services, analysis services, PowerBI, integration services, or any other data visualization tools.
12. Technological Savvy/Analytical Skills:  Technologically adept and especially demonstrate an understanding of database and computer software.
13. Interpersonal Skills: A suitable candidate for this position will be a team-builder, be result-oriented, be proactive and self-driven requiring minimal supervision, be open and welcoming to change, be a creative and strategic thinker, have innovative problem-solving skills, be highly organized, have an ability to handle multiple simultaneous tasks prioritize and meet tight deadlines, and demonstrate calmness in times of uncertainty and stress.
14. People Skills:  a people person who is able to form strong, lasting, and meaningful bonds with others people. This will make him an approachable and trustworthy individual who junior personnel readily follow and who senior Data and Analytics executives and stakeholders trust and who’s insights they give credit to, making execution of his duties much easier.
     

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Job Purpose:   

Reporting to Head Data Science, the Data Scientist will apply data mining techniques and conduct statistical analysis to large, structured and unstructured data sets to understand and analyse phenomena. Model complex business problems, discovering insights and opportunities through statistical, algorithmic, machine learning and visualisation techniques, working closely with internal and external stakeholders, data, technology and support teams to turn data into critical information used to make sound business decisions. Execute intelligent automation and predictive modelling.

Job Responsibilities/ Accountabilities:

1. Support in the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organisations goals.
2. Perform data pre-processing including data manipulation, transformation, normalisation, standardisation, visualisation and derivation of new variables/features.
3. Document business requirements
4. Develop model documentation for the purpose of model validation
5. Develop dashboards and presentations for business insights using tools like  PowerBI and Microsoft power point
6. Utilise advanced data analytics and mining techniques to analyse data, assessing data validity and usability; reviews data results to ensure accuracy; and communicates results and insights to stakeholders.
7. Designs various mathematical, statistical, and simulation techniques to typically large and unstructured data sets in order to answer critical business questions and create predictive solutions which drive improvement in business outcomes. Drives analytics and insights across the organisation by developing advanced statistical models and computational algorithms based on business initiatives
8. Use data profiling and visualisation techniques using tools to understand and explain data characteristics that will inform modelling approaches. Communicate data information to business with various skill levels and in various roles, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights and defend recommendations.
9. Create, maintain and optimise modelling solutions that enable the forecast of quality data outcomes. Ensures that volumetric predictions are modelled so that resource requirements are optimally considered. Develops and maintains optimal evaluation techniques to ensure that modelled outcomes are rigorous and creates model performance tracking. Drives sustainable and effective modelling solutions.
10. Provide  input into Data management and modelling infrastructure requirements and adheres to the organisations’s infrastructure development processes, including the management of User Acceptance Testing (UAT). Conducts regression testing across all relevant systems as required.
11. Build machine learning models from and utilises distributed data processing and analysis methodologies. Competent in Machine Learning programming in R or Python, with supplementary still in Java, etc. Familiar with the Hadoop distributed computational platform, including broader ecosystem of tools such as HDFS / Spark / Kafka

Qualifications and Experience

1. Degree in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field.
2. Working experience in the finance industry via direct employment or consultancy
3. 3-5 years’ experience in working with structured and unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data. Experience with common data science toolkits. Experience with data visualisation tools, such as Power BI, Tableau, etc.
4. Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Power BI; Qlikview; Tableau; SSIS SSRS, R, Python, JSON , C#, Java, C++, HTML
5. Experience with the use of GIT
6. Proven development experience in software and software engineering. Understanding of financial services data processes, systems, and products. Experience in technical business intelligence. Knowledge of IT infrastructure and data principles.
7. Project management experience. Exposure to governance and regulatory matters as it relates to data. Experience in building models (credit scoring, propensity models, churn, etc.).
8. A suitable candidate will also have had experience working with and influencing and possess vast experience and expertise with probability and statistics, inclusive of machine learning, experimental design, and optimization. As a bonus he will also have had experience working with Hadoop.
9. Communication Skills: Communication skills will also be a necessity for the Data Scientist. He must be able to convey important messages and information
10. Ms Office/Software:  Outstanding skills in the use of Ms Word, Ms Excel, PowerPoint, and Outlook, which will all be necessary for the creation of both visually and verbally engaging reports and presentations, for senior data science management, executives, and stakeholders.
11. The candidate must also demonstrate exceptionally good skills in SQL server reporting services, analysis services, PowerBI, integration services, Salesforce, or any other data visualization tools.
12. Technological Savvy/Analytical Skills:  Technologically adept and especially demonstrate an understanding of database and computer software.
13. Interpersonal Skills: A suitable candidate for this position will be a team-collaborator, be result-oriented, be proactive and self-driven requiring minimal supervision, be open and welcoming to change, be a creative and strategic thinker, have innovative problem-solving skills, be highly organized, have an ability to handle multiple simultaneous tasks prioritize and meet tight deadlines, and demonstrate calmness in times of uncertainty and stress.
14. People Skills:  A people person who is able to form strong, lasting, and meaningful bonds with others people. This will make him/her an approachable and trustworthy individual who junior personnel readily follow and who  Data and Analytics colleagues and stakeholders trust and who’s insights they give credit to, making execution of his duties that much easier.