Senior Data Scientist
Коротко
Owns the modelling component of client engagements from problem definition to production deployment, delivers reproducible pipelines, deploys models on · Needs: 5+ years applied data science with models in production, hands-on MLflow, professional fluency in English, overlap with Gulf Standard Time (UTC+4).
Описание от работодателя
Quantum One is an Abu Dhabi-based AI consultingand solutions company. We design and deployAI/MLsystems for industrial clients across theenergy, logistics, manufacturing and infrastructuresectorsin the UAE.
The Senior Data Scientist is accountable for themodelling component of client engagements fromproblemdefinition to production deployment.
Key responsibilities Translate client operational objectives into well-defined modelling tasks with agreed successmetrics,constraints and data requirements.
Select and justify analytical methodsappropriate to industrial problems —time-series analysis,anomaly detection,forecasting, optimisation, computer vision— and develop custom approacheswherestandard methods are insufficient.
Communicate methodology, assumptionsand limitations to client stakeholders,including non-technical operations leadership.
Deliver reproducible modelling pipelinesthat colleagues can execute andextend independently.
Deploy models to production in collaborationwith the engineering team on Databricks:MLflowtracking and registry, inferenceservices, monitoring and retraining.
Candidate profile A minimum of five years of applied datascience with models in production, preferablyin industrial,energy, logistics ormanufacturing environments.
Sound statistical foundations, includinguncertainty and causal reasoning appliedto operational data.
Demonstrated depth in time-series modellingand anomaly detection; working knowledgeof optimisationmethods (OR, RL).
Hands-on experience with MLflow andstandard production ML workflows.
Professional fluency in English.
Terms Fully remote; overlap with Gulf StandardTime (UTC+4) is required.
Contractor engagement;competitive compensation.
Candidates are invited to apply via LinkedInor by email.
Referrals are welcome.