Job Description

Aa a Senior Solution Consultant, you will own the technical win in the sales cycle. From the first workshop through proof-of-value and hand-over, you will map customer pain points, design data-collection strategies down to sensor level, interpret model outputs and demonstrate clear return on investment. You are the bridge between DataMind AI's analytics and the customer's reliability, maintenance and operations teams.

Key Responsibilities:

Lead discovery sessions with reliability, instrumentation, OT and operations stakeholders to define use cases, success metrics and data readiness. Audit existing sensors and instrumentation (vibration, temperature,,, oil analysis, pressure) and recommend additions or upgrades where needed. Coordinate proof-of-value projects: work with internal data-science and implementation teams to ensure data ingestion and signal-quality validation; interpret results and present clear business value. Translate findings into clear business impact for technicians, engineers and executives. Build ROI briefs and partner with Account Executives on proposals, competitive positioning and commercial negotiations. Produce comprehensive technical hand-off packages for implementation and customer-success teams; remain the subject-matter expert until initial KPIs are met. Capture market feedback on emerging African mining needs (mobile-equipment health, dragline analytics, ESG reporting) and relay insights to Product and Engineering.



Requirements:


At least 5 years in condition monitoring, reliability engineering or predictive-maintenance analytics within mining. Hands-on experience analyzing vibration, lubrication, thermography or comparable data on crushers, mills, conveyors and mobile fleets (Caterpillar, Komatsu, Liebherr, draglines, dozers). Practical knowledge of sensor selection, installation and certification. Bachelor's degree in Mechanical, Electrical, Instrumentation or Mining Engineering (or equivalent industry experience). Familiarity with industrial analytics suites such as AVEVA Predictive Analytics, Aspen Mtell, OSIsoft PI, GE APM or similar. Proven success conducting demos or proof-of-value projects and converting technical validation into signed deals. Strong written and verbal communication skills; able to present complex engineering insights to all organizational levels. Ability to meet mine-site safety requirements and undertake frequent short-notice travel.

Advantages:

Experience deploying machine-learning models or digital twins in heavy-industry environments. Knowledge of ISO 55000, reliability-centered maintenance and condition-based maintenance programmes. Exposure to mobile-fleet health systems (Caterpillar MineStar, Modular Mining MineCare). * Basic data analysis skills (Excel / PowerBI / Python) for ad-hoc data quality and KPI checks.