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

SeekUp
London
1 year ago
Applications closed

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 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.