Senior Data Scientist and Lead

Overview

Invenda Group AG is an international technology company transforming automated retail through intelligent software and hardware solutions. With teams across Switzerland, US, Germany, Serbia, and Hong Kong, we are growing fast and continuously improving our internal operations.

We are forming a new Stars team, responsible for building precise, production-grade AI models and extracting deep statistical insights from our Datalake/BI platform. These insights directly help our customers increase revenue, optimize operational efficiency, and reduce maintenance costs of their global machine fleets.

We are looking for a Senior Data Scientist (7–20+ years) to join this core team and shape the next generation of Invenda’s smart-insight products.

• AI & Analytics Delivery:
  Develop predictive, prescriptive, and generative AI models across domains such as demand forecasting, personalization, maintenance prediction, vision models, and vending-specific user behavior.
• Analyze high-volume POS, telemetry, sensor, and DOOH data to generate actionable insights for customers.
• Own the full ML lifecycle: exploration, feature engineering, training, deployment, monitoring, and continuous refinement.

• Technical Leadership:
  Act as the technical lead of the Stars team, guiding DS, Data Engineering, and Backend engineers.
• Set engineering best practices, coding standards, and model governance across the team.
• Lead architecture decisions for AI, MLOps, data pipelines, and system integrations.
• Review designs and code, ensure consistency, quality, and long-term maintainability.
• Translate business goals into technical roadmaps and measurable deliverables.

• Collaboration & Strategy:
  Work closely with Product, BI, Platform Engineering, and Machine teams to define data needs and model capabilities.
• Identify opportunities for new insights, model-based products, and automation improvements.
• Communicate results clearly to internal stakeholders and external customers.

• Personal & Leadership
  
  Skills:
  
  Excellent communication and structured reporting; full working proficiency in English is required.
• Strong leadership presence: capable of aligning the team, setting priorities, and driving execution.
• Empathetic mentor who helps engineers grow, gives clear feedback, and fosters an open, collaborative culture.
• Highly proactive, transparent and accountable—comfortable owning complex problems end-to-end.
• Able to challenge assumptions, introduce improvements, and influence decisions at team and organizational level.

• Expert-level experience in ML systems, statistics, time-series modeling, and advanced algorithms.
• Hands-on experience with LLMs, embeddings, RAG-style systems, and generative ML.
• Ability to design cost-efficient, scalable ML architectures and pipelines.

• Strong software engineering fundamentals:
• Agile practices
• TDD
• Algorithms & Data Structures
• OOP/OOD principles

• Hands-on experience in large-scale cloud environments (Azure preferred; AWS/GCP acceptable).
• Familiarity with IoT data flows, microservices and serverless architectures.
• Proficiency with REST/gRPC APIs; exposure to C#/.NET ecosystems is a plus.
• Advanced RDBMS/No
  
  SQL knowledge: indexing, optimization, partitioning, query tuning.
• Experience with modern data ecosystems:
  Databricks, Spark, Azure Data Factory, Snowflake.
• Strong expertise in either SQL or Mongo
  
  DB (expert level in at least one).

• Observability and monitoring (Application Insights, Datadog).
• Experience with retail analytics, vending KPIs, IoT telemetry or DOOH ecosystems.

• Lead a new greenfield analytics team and shape Invenda’s core data & AI capabilities.
• Build high-impact models used across smart vending, retail and DOOH networks worldwide.
• Work in a transparent, fast-moving engineering culture that values ownership and innovation.