{"id":1585814,"url":"https://alion.io/job/cicinsurancegroup-senior-data-scientist","title":"Senior Data Scientist","company":{"id":2467372,"name":"CIC Insurance Group","domain":"cicinsurancegroup.com","url":"https://alion.io/company/cicinsurancegroup","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Kenya"],"countries":["KE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":15500,"max_usd":41000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"closed","first_seen_at":"2026-09-14T07:28:05Z","employer_posted_date":null,"last_verified_at":"2026-10-29T17:48:20Z","board_verified":false,"closed_at":"2026-10-29T17:48:20Z","days_open":45,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":45},"description":"IT Jobs. CIC Insurance Jobs. Senior Data Scientist. Building predictive models, analyzing insurance data, and deploying AI solutions, requiring a Data Science/Statistics Degree, machine learning expertise, and 5+ years experience.\n\nAbout the Role\n\nReporting to the Data & Analytics Manager, the Senior Data Scientist will be responsible for developing, deploying, and maintaining data analytics, data science, machine learning, and artificial intelligence solutions that support business decisions.\n\nThe role covers the full analytics lifecycle, from exploratory analysis and business intelligence reporting through to feature engineering, model building, deployment, and performance monitoring, with a working understanding of how the underlying data pipelines and warehouses are structured. The role will collaborate with colleagues across the Data & Analytics function and with other stakeholders to build data science and analytics solutions into products, services, customer propositions, and digital channels.\n\nKey Responsibilities\n\nPerform exploratory data analysis to answer business questions, identify trends, and surface issues that need attention.\n\nDevelop, validate, deploy, and maintain statistical, machine learning, and AI models across customer analytics, segmentation, retention, forecasting, risk, fraud, and optimisation use cases.\n\nTranslate business and customer needs into analytical problems and data science solutions.\n\nPerform data exploration, feature engineering, model selection, validation, and performance monitoring.\n\nBuild and maintain machine learning pipelines, and deploy solutions into business processes, products, and digital channels.\n\nOwn end to end reporting work, from gathering requirements with business teams through to building dashboards, reports, and visualisations that support business decisions.\n\nWork with data engineering colleagues on data quality, pipeline structure, and warehouse design where it affects analytical or model work.\n\nMonitor model performance, data quality, and drift, and keep solutions documented, explainable, and aligned with governance requirements.\n\nCommunicate findings and recommendations to technical and non-technical stakeholders.\n\nQualifications\n\nBachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative discipline from a recognised institution.\n\nMinimum of five (5) years of experience in Data Analytics, Business Intelligence, or Data Science.\n\nComfortable working across the analytics stack, from data analysis and BI reporting to model building.\n\nStrong proficiency in R and/or Python, advanced SQL, and applied statistics, including inference, hypothesis testing, regression, and experimental design.\n\nStrong understanding of machine learning techniques and algorithms, including model selection, validation, and optimisation.\n\nExperience working with relational databases, data warehouses, and large datasets, including both structured and unstructured data.\n\nExperience building dashboards and reports using tools such as Power BI, Tableau, or equivalent.\n\nExperience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud is an added advantage.\n\nStrong analytical, problem solving, communication, and stakeholder management skills.\n\nHow to Apply\n\nClick here to 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