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Satori Analytics

AI-powered decision analytics for enterprises

Presales Engineer - Data & AI

Pre-Sales Solution EngineeringPosted on Nov 2
Full-timeNo salary listed

About the Job

Requirements

  • A Bachelor of Science in Computer Science, Engineering, Mathematics, or Physics or a related field, plus a Master of Science in Data Science, Computer Science, or another STEM discipline.
  • At least 6 years delivering data and artificial intelligence projects, ideally in a consultancy, across both data engineering and data science, including at least 2 years in a client-facing role scoping and estimating projects.
  • Expert SQL and Python, strong PySpark, ETL/ELT using Azure Data Factory or Databricks, warehouses and lakehouses such as Fabric, Databricks, or Snowflake, relational and NoSQL databases, data modelling (star schema, data vault, SCD), and understanding the effort involved in BI semantic models and dashboards.
  • A solid grasp of machine-learning learning paradigms and algorithm families; hands-on exploratory data analysis, feature engineering, and explainability using the Python stack; and at least two real-world machine-learning projects delivered personally, such as churn, CLV, forecasting, recommenders, pricing, or segmentation.
  • Hands-on experience with generative AI (RAG and agentic workflows), ready-made AI services such as OCR, sentiment, and transcription, and production-grade Python, including understanding how to progress from notebook to enterprise-grade software.
  • Strong knowledge of Azure, AWS, or GCP, including the pricing of their data and AI services, plus Git, Docker, and Agile delivery.
  • A track record of bottom-up estimates and staffing plans using work breakdown structures, three-point estimation, or past-project benchmarks, and commercial understanding of how effort, risk, and contingency affect price and margin.
  • Clear, structured writing and confidence explaining trade-offs to executives and defending scope.
  • Fluent English.

Responsibilities

  • Lead implementation-effort estimates for Data & AI proposals, from early sizing through the final commercial offer.
  • Build work breakdowns across ingestion, pipelines, modelling, lakehouse, BI, machine learning, MLOps, testing, deployment, and project management; convert effort by role into staffing plans, timelines, and milestones.
  • Make assumptions, dependencies, exclusions, and risks explicit; size contingency for data quality, integration, and model uncertainty; and estimate cloud and licence running costs.
  • Lead discovery workshops with client executives and technical teams, design end-to-end architectures with Technical Leadership, and identify what is infeasible, unready, or not worth building before committing.
  • Write technical sections of proposals and RFP/tender responses, build quick proofs of concept and demos with the presales team, and defend solutions and estimates in client meetings.
  • Give Delivery a clear scope, estimate, and assumptions log, and stay close to early delivery.
  • Maintain estimation models, templates, and benchmarks; calibrate them against actual project results; and build reusable reference architectures and accelerators.

Desired Qualifications

  • Greek language ability.
  • A PhD in a STEM field.
  • Kubernetes and MLOps tooling for deploying and monitoring models in production.
  • Certifications such as Azure Solutions Architect, Databricks, Snowflake, or Microsoft Fabric.
  • Experience bidding for public-sector tenders or large enterprise RFPs.

About the Company

Satori Analytics

AI-powered decision analytics for enterprises

Satori Analytics creates data and AI solutions that help organizations make better decisions. It develops and deploys enterprise-grade AI systems that integrate data pipelines, analytics, and machine learning models into clients’ operations so managers can gain clear, data-backed insights. Unlike firms that only talk about AI, Satori emphasizes delivering production-ready AI solutions across industries such as Energy, Financial Services, Consumer Goods, Manufacturing, and Government, with deployments in more than 15 countries and 100+ production-grade AI solutions. The company differentiates itself through its track record of real deployments and its focus on practical impact rather than theoretical capabilities. Its goal is to provide clarity in decision making by making AI-driven insights readily usable for business leaders and operators.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2014

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