DATA SCIENTIST-ASSISTANT MANAGER JOB
Reporting to the Manager – Business Intelligence (B.I) & Analytics, the Data Scientist’s role will:
- Help to create and maintain a state-of-the art Big Data platform for deep analytics, that will generate business insights in line with the Central Bank of Kenya Mandate.
- Consultatively gather requirements by understanding the business challenges attempted to be resolved in reference to the data available and data to be acquired.
- Model business problems, discovering insights and opportunities through statistical, algorithmic, machine learning and visualisation techniques, working closely with clients, data and technology teams to turn data into critical information used to make sound business decisions.
- Assist in applying data mining techniques and conduct statistical analysis to large, structured and unstructured data sets to understand and analyse different phenomena.
- Monitor and optimize performance of developed models by driving experiments, benchmarking, etc.
Key Duties and Responsibilities
- Delve into data from different systems, structured and unstructured, both batch and real time, to discover hidden relationships and useful information.
- Assist the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organisations goals. Perform data pre-processing including data manipulation, transformation, normalisation, standardisation, visualisation and derivation of new variables/features. Utilize advanced data analytics and mining techniques to analyse data, assess data validity and usability; review data results to ensure accuracy; and communicate results and insights to stakeholders.
- Assist 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. Assist analytics and insights across the organisation by developing advanced statistical models and computational algorithms based on business initiatives.
- Code, test and maintain scientific models and algorithms and identify trends, patterns, and discrepancies in data and determine additional data needed to support insight. Process, clean and verify the integrity of data used for analysis.
- 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 respective stakeholders, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights and defend recommendations under the supervision of data scientists.
- Utilize the appropriate data storage and data mining tools to ensure value can be extracted from the sourced data. Mine data using state-of-the-art methods and enhances data collection procedures to include information that is relevant for building models.
- Identify recurring problems and bottlenecks that might be improved, collaborate with System Administration and cross functional teams to impart new technologies in the analytics, infrastructure, or further research into statistical methodology.
- Provide engagement and drive change through influence and the strategic use of data across the Bank, develop big data and machine learning models for various areas of the business.
- Be an analytics subject matter expert, developing and driving adoption of Business Intelligence & Analytics using Big data, ETL and Analytical tools for the business and management information.
- Liaise and collaborate with the Data Science Team providing support to stakeholders in the department for its data centric needs. Collaborate with subject matter experts to spot viable use cases, select the relevant sources of information, and translate the business requirements into data mining/science outcomes.
- Present findings and observations to the team for development of recommendations.
- Support various mathematical, statistical, and simulation techniques to answer business questions within specific areas of focus. Develop modelling solutions that enable the forecast of quality data outcomes.
- Ensure that volumetric predictions are modelled so that resource requirements are optimally considered.
- Support reporting production and ensure sustainable and effective modelling solutions.
- Support and implements operational plans, rules, methodologies and coding initiatives. Support and implement the strategy for deploying into production automation software so that it is accurate and well maintained.
- Technology & Architecture
- Assist in building machine learning models and utilise distributed data processing and analysis methodologies.
- Competent in Machine Learning programming in R or Python, with supplementary skills in Matlab, Java, etc. Familiar with the Hadoop distributed computational platform, including broader ecosystem of tools such as HDFS / Spark / Kafka.
- Bachelor’s Degree in Information Studies, Mathematics, Statistics, Economics, Information Technology, Computer Science, Electrical /Electronics Engineering.
- Post Graduate degree in Information Studies, Mathematics, Statistics, Economics, Information Technology, Computer Science, Electrical / Electronics Engineering is an added advantage.
- Certifications or professional memberships in any of the following areas:
- Proficiency in application and web development.
- Structured and Unstructured Query languages e.g. SQL, Qlik/Qlikview, Tableau, Python, C#, Java, C++, HTML.
- Completion of online coursework in Data Science, Artificial Intelligence/Machine Learning through Udemy, Coursera, Udacity, edX, etc. is an added advantage.
At least 5 years’ relevant work experience with hands on experience in Data Science and Data Analytics.
- Technology Business Partnering
- Proven hands on track record of translating business problems into analytical framework, developing analytical plans for answering complex problems and delivering analytical insights, to add value to business teams.
- Excellent communication skills, with the ability to present technical results to non-technical audiences.
- 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.
- Project management experience.
- Experience in building models (credit scoring, propensity models, churn, etc.).
- Data and Business Analysis
- Experience in working with 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, such as SAS, R, SPSS, etc.
- Solid hands-on understanding of Database, Data Modelling, SQL Developer, Data Warehouse concepts and advanced analytics concepts. Implementation experience is preferred.
- Hands-on expertise in data manipulation via the use of structured data tools (e.g., SQL), & unstructured data tools and platforms (e.g., Spark, Hadoop, Hive, etc.), with capability to do exploratory analysis on both sets of data
- Experience with data visualisation tools, such as Power BI, Tableau, etc.
- Knowledge of Database query writing and reporting tools such as SQL Reporting, SQL Developer, Excel, Toad etc.
- Experience with System Development Lifecycle and IT best practices and Change Management principles.
Behavioral / General Competencies
- Strong analytical and creative problem-solving skills.
- Curiosity, creativity, innovative and an empirical mindset.
- Team player.
- Demonstrated ability to work in a large, matrixed organization, successfully influencing others & building relationships through exceptional communication skills.
- Excellent written and verbal communication/presentation skills.
- Excellent ability to multi-task and manage simultaneous projects and initiatives.
- Strong planning, organization, critical thinking, decision-making skills and problem-solving aptitude.