{"id":1871100,"url":"https://alion.io/job/teraco-lead-data-scientist","title":"Lead Data Scientist","company":{"id":57366,"name":"Teraco","domain":"teraco.co.za","url":"https://alion.io/company/teraco","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"MCI DirectHire","truth_index":{"grade":"A","score":88,"open_postings":18,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-15T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["South Africa"],"countries":["ZA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":31000,"max_usd":69000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":662},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-02-19T12:00:00Z","employer_posted_date":"2026-10-04","last_verified_at":"2026-10-16T02:43:17Z","board_verified":true,"closed_at":null,"days_open":238,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":237},"description":"Description\nPurpose of the Role\nThe Lead Data Scientist is responsible for:\nShaping and executing Teraco's data and analytics strategy,\nDriving business innovation through the effective use of data and analytics,\nFostering a data-driven and model-driven culture,\nEnsuring that data and analytics capabilities support business objectives.\nMain Functions of the Job\nArtificial Intelligence\nCollaborate with stakeholders to identify opportunities for data and analytics driven solutions.\nLead the design, implementation, and use of artificial intelligence / machine learning and analytics.\nDesign and incorporate best practices of “MLOps” for managing the lifecycle of models / solutions. E.g. data preparation, model training, feature selection, evaluation, model selection, deployment, monitoring, maintaining, code version control, etc. \nData Engineering (incl. Data Management)\nDesign and help build a modern data platform with a robust data governance framework.\nIncorporate best practices of managing “big data” (i.e. high volume, high velocity, high variety).\nEstablish and execute processes for data quality, metadata management, and data lifecycle management.\nEnsure adherence to relevant data privacy and regulatory requirements.\nLeadership\nServe as a trusted advisor to the business, providing insights and recommendations based on data.\nAdvocate for data-driven decision-making across Teraco.\nDrive a culture of innovation and continuous learning and teaching - both within the Data & Analytics team and within the broader Teraco business.\nStay on top of emerging trends in data science, AI, and analytics.\nMentor and develop team members and stakeholders, promoting professional growth and expertise.\nValue\nMeasure and communicate the business impact of data and analytics initiatives to stakeholders.\nContinuously optimise data and analytics processes for efficiency and effectiveness.\nRequirements\nSkill Requirements\nExcellent written and verbal communication skills.\nClearly articulates ideas and thoughts.\nActive listening and the ability to understand complex requirements.\nProblem-solving mindset with a proactive approach.\nCapability to work independently and as part of a team.\nSelf-motivated and professional demeanour.\nLeadership qualities with high tolerance and patience.\nCommitment to self-development and continuous learning.\nAttention to detail and accuracy.\nGood prioritisation and organisation skills.\nComplies with policies and procedures.\nQualifications and Experience\nDegree in Mathematics, Data Science, Statistics, Computer Science, or a related field.\nPost graduate qualifications in data science, statistics, machine learning, data engineering, computer science, or related fields.\nMinimum of 10 years’ experience in data science, machine learning, AI.\nDeep experience with the core tools of 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