Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Sr. Solutions Architect (Cloud Data, ELN, LIMS) - Europe remote

SeekUp
London
9 months ago
Applications closed

Related Jobs

View all jobs

Sr. Data Engineer

Sr Data Scientist (London)

Remote (Sr.) Data Engineer (m/f/d)

Associate Director, AI Data Scientist

Sr. AI Data Engineer (UK Remote)

Sr Data Analyst New York, New York

Senior Solutions Architect · Remote Europe · Full-time

Our Client is a leader in providing advanced cloud-based solutions that transform how scientific data is managed and utilized. Dedicated to improving and extending human life, Our Client combines a cutting-edge, collaborative cloud platform with deep expertise to drive innovation and accelerate scientific breakthroughs. By enabling seamless integration of data, Our Client empowers scientists and researchers to unlock new possibilities through AI-driven insights and next-generation laboratory solutions.

Role Overview

As a Solutions Architect, you will partner with clients in the pharmaceutical and biotechnology sectors to design and deliver innovative solutions that address complex data challenges. Your role will involve collaborating with R&D teams, analyzing data environments, developing tailored strategies, and ensuring seamless integration with client systems.

This is a highly technical role that bridges the gap between business and technology, requiring you to translate complex scientific and IT requirements into impactful solutions. You will collaborate with internal teams, including sales, engineering, and product, while fostering strong relationships with external stakeholders.

Key Responsibilities

Client Engagement:

  • Work closely with laboratory teams, researchers, and IT professionals to understand workflows and challenges. Develop solutions that address their needs using Our Client’s platform.
  • Act as a trusted advisor, guiding clients through the implementation process and supporting their adoption of our tools.
  • Gather and synthesize feedback from clients to continuously enhance the platform and related solutions.

Solution Design:

  • Develop customized solutions that map technical capabilities to business objectives.
  • Provide strategic insights into how seamless data integration and AI tools can improve laboratory operations and outcomes.
  • Collaborate with internal product and engineering teams to ensure solutions align with client requirements and long-term vision.

Sales Enablement:

  • Support sales efforts by showcasing the value of Our Client’s platform through tailored presentations, product demonstrations, and consultations.
  • Develop responses to Requests for Information (RFIs), Requests for Proposals (RFPs), and Statements of Work (SOWs).
  • Identify opportunities to deepen client engagement and expand platform adoption.

Project Coordination:

  • Ensure project timelines and deliverables are met by effectively managing internal and external stakeholders.
  • Communicate technical solutions in an accessible manner, facilitating alignment among diverse teams.
  • Drive customer success by assisting with change management and ensuring smooth integration.

Skills and Expertise

Technical Proficiency:

  • Strong background in scientific data management, with a focus on life sciences research.
  • Expertise with laboratory systems, including but not limited to ELN, LIMS, CDS, and data visualization tools.
  • Knowledge of pharmaceutical R&D processes, from discovery to manufacturing. Experience with large molecule or emerging modalities is a plus.
  • Familiarity with cloud platforms and data architecture, particularly AWS, is preferred.

Soft Skills:

  • Excellent communication skills, with the ability to simplify complex technical concepts for non-technical audiences.
  • Proven ability to build relationships and collaborate effectively with diverse stakeholders.
  • Strong problem-solving and negotiation skills, with a focus on delivering value for all parties.

Business Acumen:

  • Ability to calculate ROI for proposed solutions and demonstrate the business impact of Our Client’s offerings.
  • In-depth understanding of challenges and trends within the life sciences sector.

Requirements

  • A scientific background or at least 8 years of experience in life sciences R&D IT or informatics. Experience as a bench scientist or data scientist is a significant advantage.
  • Demonstrated success in enterprise sales within the pharmaceutical industry.
  • A passion for innovation, intellectual curiosity, and a desire to thrive in a fast-paced, dynamic environment.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Jobs

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.