SAS Programmer in Clinical Trials

PSI CRO
Oxford
1 month ago
Applications closed

Related Jobs

View all jobs

Junior Data Scientist

Entry Level Data Analyst

Entry Level Data Analyst

Entry Level Data Analyst

Entry Level Data Analyst

Entry Level Data Analyst

Job Description

Actual position's title: Clinical Data Scientist

Reporting to the Clinical Data Science Manager, the Clinical Data Scientist is an integral part of our team here at PSI. You will work with clinical trials patient and operational data, develop new data solutions and set up Risk-based Monitoring systems in Process Improvement department.

Hybrid work in Oxford

  • Participate in selection of the Risk-Based Monitoring (RBM) system and provide relevant training to the project team and/or Sponsor
  • Set up and maintain RBM systems, collaborating with the Central Monitoring Manager
  • Manage complex datasets from multiple sources, including data extraction, transformation, and loading into PSI data platform
  • Program and produce data listings, tables, and figures for Clinical Data Reviewers and Central Monitoring Managers
  • Calculate Key Risk Indicators and Quality Tolerance Limits, applying advanced analytical techniques to identify data trends for Centralized Monitoring
  • Collaborate cross-functionally to identify study challenges and develop data solutions using advanced analytics
  • Communicate data findings and solutions to stakeholders effectively
  • Contribute to the development of databases, software products, processes, and Quality System Documents for Centralized Monitoring


Qualifications

Must have:

  • Degree in Data Science, Mathematics, Statistics, Computer Science or equivalent
  • Minimum 4 years of SAS programming experience in Clinical/Pharmaceutical domain
  • At least 2 years of experience in data engineering area including one or more of the following: relationship databases, data warehousing, data schemas, data stores, data modeling, testing, validation and analysis
  • Full professional proficiency in English
  • Strong analytical and logical thinking
  • Communication and collaboration skills

Nice to have:

  • SAS programming experience with SQL programming
  • SAS programming experience in Biostatistics Department or Clinical Programming Department
  • Knowledge of CDISC SDTM
  • Experience with CluePoints RBM system
  • Knowledge of statistical methods and techniques for analyzing data
  • Experience using Machine Learning technics and products testing and validation



Additional Information

What we offer:

  • We value your time so the recruitment process is as quick as 3 meetings
  • We'll prepare you to do your job at highest quality level with our extensive onboarding and mentorship program
  • You'll have excellent working conditions - spacious and modern office in convenient location, and friendly, supportive team who love to hang out together 
  • You'll have permanent work agreement at a stable, privately owned company
  • We care about our employees - aside from competitive salary, you'll have good work-life balance with flexible working hours and additional days off, life and medical insurance, sports card, lunch card 
  • We're constantly growing which means opportunities for personal and professional growth 

Make the right call and take your career to a whole new level. Join the company that focuses on its people and invests in their professional development and success.

Please submit your CV in English

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

Jobs Careers

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Jobs

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

🍪 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.