Mid-Level Data Scientist

Tezza Business Solutions is seeking a talented and analytically driven Mid-Level Data Scientist to join its growing technology team in Nairobi. In this role, you will harness the power of data mining, statistical analysis, and machine learning to extract meaningful insights from large, structured and unstructured datasets. You will play a pivotal role in translating complex data into actionable intelligence that drives sound business decisions for both internal teams and clients.

Working at the intersection of data engineering, business strategy, and intelligent automation, you will collaborate closely with clients, technology teams, and cross-functional stakeholders to design predictive models, drive analytics initiatives, and implement automation solutions that deliver measurable business outcomes.

• Gather, assess, and curate datasets that accurately reflect organisational goals and analytical requirements.
• Perform comprehensive data pre-processing including manipulation, transformation, normalisation, standardisation, and feature engineering.
• Apply advanced analytics and data mining techniques to evaluate data validity, uncover trends, and communicate actionable insights to diverse stakeholder groups.
• Design and implement mathematical, statistical, and simulation models on large, unstructured datasets to answer critical business questions and power predictive solutions.
• Develop advanced statistical models and computational algorithms aligned to business initiatives, driving analytics adoption across the organisation.
• Code, test, and maintain scientific models and algorithms; identify patterns, discrepancies, and data trends; and determine additional data requirements.
• Utilise data profiling and visualisation tools to interpret data characteristics and communicate findings clearly to audiences with varying technical backgrounds.
• Create, optimise, and maintain modelling solutions that forecast quality data outcomes and ensure volumetric predictions account for resource requirements.
• Develop and maintain rigorous model evaluation techniques, performance tracking frameworks, and sustainable modelling pipelines.
• Design, implement, monitor, and maintain an operational Intelligent Automation (IA) plan including rules, methodologies, and coding initiatives to support remediation efforts.
• Co-ordinate and execute a comprehensive strategy for productionalising automation software to ensure accuracy, reliability, and maintainability.
• Enhance data collection procedures and mine data using state-of-the-art methods to continuously improve the quality of inputs into data models.
• Provide input into data management frameworks, governance standards, and best practices across the organisation.

• Must demonstrate at least 3–5 years of hands-on experience applying machine learning algorithms (e.g. regression, classification, clustering, neural networks) to solve real-world business problems.
• Must be proficient in Python and/or R for statistical modelling, data manipulation, and model deployment.
• Must be able to design, build, and validate predictive models and evaluate their performance using appropriate metrics (RMSE, AUC, F1-score, etc.).
• Must be able to wrangle and analyse large structured and unstructured datasets using tools such as SQL, Spark, or Hadoop.
• Must demonstrate experience building and presenting data visualisations using tools such as Power BI, Tableau, or Matplotlib to non-technical audiences.
• Must have practical experience with intelligent automation concepts and tools (RPA, rule-based automation, or ML-driven automation).
• Must be capable of communicating complex analytical findings with clarity and confidence to clients, business leaders, and technical teams.
• Must demonstrate experience in data pre-processing pipelines, feature engineering, and ensuring data integrity throughout the modelling lifecycle.
• Familiarity with cloud platforms (AWS, Azure, or GCP) for model deployment is a strong advantage.
• A Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field is required; a Postgraduate qualification is an added advantage.

Tezza Business Solutions offers a competitive remuneration package commensurate with experience. Based on Kenyan market benchmarks for mid-level data science professionals, the estimated monthly salary range is KES 120,000 – 200,000. The final offer will reflect your qualifications, depth of experience, and demonstrated technical competency.

Ideal candidate: You are a curious, results-oriented data professional with 3–5 years of experience applying data science techniques in a commercial or consulting environment. You thrive in collaborative settings, can manage multiple analytical workstreams, and are passionate about turning messy data into clear, actionable business value. Experience working with financial services, telecoms, or technology clients is a strong advantage.

Do NOT apply if: You have fewer than 3 years of hands-on data science experience, if your background is purely theoretical or academic with no applied modelling work, or if you are not comfortable presenting and defending analytical recommendations directly to business clients.

• Prepare an updated CV clearly highlighting your data science projects, tools used, and measurable outcomes achieved.
• Write a brief cover letter (no more than one page) explaining your experience with predictive modelling and intelligent automation.
• Submit your application through the Tezza Business Solutions careers portal or the job platform where this posting is listed.
• Shortlisted candidates will be contacted for a technical screening interview followed by a practical assessment.
• Only shortlisted applicants will be contacted. If you do not hear back within three weeks of applying, consider your application unsuccessful for this cycle.