Director of Data Analytics
Company
Orcrist builds the Orcrist Intelligence Platform (OIP), a Kubernetes-based data intelligence system delivered as SaaS or self-hosted/on-prem (including air-gapped deployments). We run streaming and batch pipelines that power search, ML enrichment, and investigative workflows for mission-critical customers.
Role
This role combines people leadership, hands-on technical contribution, and active business development. You will lead and develop our Data Analytics team, ensure high-quality delivery across client and internal projects, and play a key role in acquiring and shaping new data-driven engagements in the commercial market.
The ideal candidate is a credible technical leader who is equally comfortable mentoring teams, designing data solutions, and representing the company externally to clients, partners, and at industry events.
What you'll do
Strategy, Project Planning & Business Development
- Contribute to the strategic development of the data function and its role within the company.
- Actively support project acquisition and pre-sales activities, including:
- Shaping data-driven project proposals
- Estimating scope, effort, and feasibility
- Supporting pricing and delivery models
- Represent the company at industry events, conferences, and trade fairs.
- Build and maintain relationships with commercial clients and partners.
- Bring in own clients and business opportunities where possible and take care of the current clients.
- Ensure smooth handover from sales to delivery and maintain senior oversight throughout project execution.
Data Leadership & Team Management
- Act as disciplinary and functional lead for the Data Analytics team.
- Build, mentor, and develop a high-performing team of data professionals.
- Monitor ongoing data projects, ensuring quality, delivery timelines, and alignment with business objectives.
- Establish best practices, standards, and methodologies across data science, analytics, and modeling work.
- Actively contribute hands-on to projects, especially in complex or high-impact phases.
- Foster a culture of technical excellence, ownership, and continuous learning.
Technical & Project Contribution
- Design and review data science solutions, architectures, and analytical approaches.