Data Analytics Associate

Imperatrix Datum Solutions Corporation
London
1 week ago
Create job alert
SUMMARY

Imaging Endpoints (IE) is an Imaging Technology and Imaging Clinical Research Organization (iCRO). We are passionately focused on our vision to Connect Imaging to the CureTM. Everything we do is aligned with this singular purpose. We work every day excited to advance imaging science, technology, and services to bring curative technologies to humankind. We have supported many of the most impactful new drug approvals in oncology, and we are seeking the most talented individuals globally that are passionate in their desire to assist us in our mission to customize each clinical trial’s imaging to optimize the opportunity to demonstrate efficacy.


Imaging Endpoints is based in Scottsdale, Arizona, with offices in Cambridge, Massachusetts; London, UK; Leiden, Netherlands; Basel, Switzerland; Hyderabad, India and Shanghai, China. We are an affiliate of HonorHealth, one of the largest healthcare systems nationally, and Scottsdale Medical Imaging Limited (SMIL/RadPartners), the largest private radiology group in the United States. We are recognized as the world’s largest and most preeminent iCRO in oncology.


The Data Analytics Associate is primarily responsible for configuring and running reports to provide visualization of data processing status to project teams and executive management.


RESPONSIBILITIES

  • Extracts, imports, exports, and integrates data from various internal and external applications/databases for analysis and/or reporting purposes
  • Assures the completeness, accuracy, and integrity of abstracted data
  • Reports results back to relevant members of the business on a regular basis
  • Prepares and presents reports of the data as scheduled or requested
  • Trains staff on interpretation of reports
  • Identifies patterns and trends in data sets
  • Problem-shoots inconsistencies with data and data collection
  • Ability to work independently and manage multiple work tasks
  • Perform other duties as assigned by the supervisor

EDUCATION AND EXPERIENCE

  • Bachelor’s degree in a science or health-related field (or equivalent combination of education and professional experience)
  • 3 – 5 years of industry (clinical CRO or pharmaceutical industry) experience required
  • Knowledge of Good Clinical Practice (GCP), Quality Assurance/Compliance in a clinical trial setting is required

SKILLS

  • Excellent conceptual thinking with ability to work cross-functionally
  • Outstanding oral and written communication and presentation skills
  • Excellent time management, organizational and prioritization skills
  • Understanding of medical imaging data in clinical trials preferred
  • Strong working knowledge of MS Office applications
  • Ability to interpret and apply regulatory guidelines and requirements

IMAGING ENDPOINTS’ TEAM CHARACTERISTICS

  • Passion to Connect Imaging to the CureTM and pursue a meaningful career by improving the lives of cancer patients through imaging
  • Strong desire to be part of a dynamic, global team working closely together and growing year after year in a rewarding environment to help humanity through imaging
  • Commitment and caring for our fellow team members, their families, and the communities IE serves – see more information about Caring Endpoints at https://imagingendpoints.com/caring-endpoints/
  • Integrity and high ethical standards; we always do the right thing
  • High intellect and ingenuity; we enjoy solving problems, finding a better way, and the challenge of making a difference by improving lives
  • Structured, organized, detail-oriented, and self-motivated; we approach each day with a detailed plan and excitement to accomplish the day’s objectives while striving to improve ourselves and IE everyday
  • Accountable; we do what we say and communicative effectively to meet deadlines; we enjoy advancing clinical trials, helping patients, and celebrating success
  • High standard for excellence; we proof our own work, hold high standards for ourselves and our team, and always prioritize quality above all else

PHYSICAL REQUIREMENTS

While performing the duties of this job, the employee is regularly required to use hands to finger, handle, or feel; reach with hands and arms and talk and hear. The employee is frequently required to sit. Specific vision abilities required by this job include close vision, color vision, ability to adjust focus.


Travel: Up to 15% both domestic and international


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analytics Associate

Data Analytics Associate - Audit Tech & Insights

IT Audit & Data Analytics Associate

Assistant Manager, Data Analytics – Forensics & Investigations

Graduate Actuarial Associate - Data Analytics & Modelling

Credit Research Associate - Data Analytics (Hybrid, Glasgow)

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.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.