1. Which is the most advanced degree you have earned?

No high school diploma

High school diploma or equivalent

Bachelor’s degree (e.g., BA, BBA, BFA, BS)

Master’s degree (e.g., MA, MBA, MFA, MS, MSW)

Specialist degree (e.g., EdS)

Applied or professional doctorate degree (e.g., MD, DDC, DDS, JD, PharmD) or doctorate degree (e.g., EdD, PhD)

Other

3. Which gender do you identify with? Please select all that apply.

Female

Male

Non-binary

Gender not listed here

I prefer not to answer

4. Which option most accurately describes your race and ethnicity? Please select all that apply.

Asian

Biracial

Black

Hispanic, Latino or Spanish Origin

Indigenous Peoples (please specify which country in “Other” below)

Jewish

Middle Eastern or North African

White

Other

I prefer not to answer

5. How old are you?

19 or younger

20 - 24

25 - 29

30 - 34

35 - 39

40 - 44

45 - 49

50 - 60

61 or older

I prefer not to answer

7. From where do you work?

100% in-office

Hybrid

100% remote

Other (e.g., if you would like to specify hybrid work)

12. How long have you worked with your current employer?

0 - 6 months

7 - 12 months

1 - 2 years

3 - 5 years

6 - 9 years

10 - 19 years

20+ years

Other (if you would like to specify the exact number of years)

13. What is your annual salary range (currency can be chosen in the next question)?

0 - 30,000

31,000 - 60,000

61,000 - 90,000

91,000 - 120,000

120,000 - 150,000

150,000 - 200,000

200,000 - 250,000

250,000 +

Other (please specify a number)

I prefer not to answer

16. What was the primary reason you transitioned to your current organisation from the previous one?

Joined the organisation directly after graduation

Better compensation and benefits

Better alignment with your personal values

Focusing on your own health and wellbeing

More growth opportunities (e.g. trainings, promotions etc.)

More intellectual stimulations (e.g. challenging work)

Improved work-life balance

More positive relationships with coworkers

Clearer and more timely communication from managers

Other

17. Which types of data do you work with? Please select all that apply.

Billing and financial information

Biometric data (e.g., fingerprints)

Demographic information

Diagnostic data

Medical imaging data

Histopathology data

Insurance information (e.g., claims data)

Medical history and electronic health records

Medications

Procedures and treatments

Sequencing and/or microarray data (e.g., GWS, proteomics, RNA-seq, spatial transcriptomics, cell repertoire)

Social media and lifestyle data

Digital health data (e.g., wearables, cognitive games)

Other

19. Can you talk about the origins of the data (e.g. data source(s), how was it generated, labeled, curated) you work with without asking another person about them?

Yes

No

I am aware of some of them.

20. In which disease areas do you work? Please select all that apply.

I don’t work in a specific disease area.

Addiction and substance abuse (e.g., alcoholism, opioid addiction)

Cancer (e.g., breast cancer, lung cancer)

Cardiovascular diseases (e.g., hypertension, coronary artery disease)

Genetic and rare diseases (e.g., cystic fibrosis, Huntington’s disease)

Immunology (e.g., lupus, asthma)

Infectious diseases (e.g., HIV/AIDS, malaria)

Mental health (e.g., anxiety disorders, depression)

Neurology (e.g., Alzheimer’s disease, Parkinson’s disease)

Sexually Transmitted Infections (e.g., gonorrhoea, HIV)

Allergies and immunodeficiencies (e.g., food allergies, common variable immunodeficiency)

Dermatological conditions (e.g., psoriasis, atopic eczema)

Dental and oral Health (e.g., gum disease, cavities)

Endocrinology (e.g., hypothyroidism, type 2 diabetes)

Gastrointestinal diseases (e.g., Crohn's disease, IBS)

Geriatric diseases (e.g., dementia, osteoporosis)

Gynaecological and obstetric conditions (e.g., endometriosis, ovarian cancer)

Haematological disorders (e.g., anaemia, leukaemia)

Ophthalmology (e.g., cataracts, glaucoma)

Orthopaedic disorders (e.g., osteoarthritis, scoliosis)

Paediatric diseases (e.g., congenital heart defects, paediatric leukaemia)

Renal diseases (e.g., chronic kidney disease, kidney stones)

Respiratory diseases (e.g., asthma, chronic obstructive pulmonary disease)

Urological disorders (e.g., benign prostatic hyperplasia, urinary tract infections)

Vector-borne diseases (e.g., Lyme disease, Zika virus)

Other

21. Which language or platform do you use? Please select all that apply.

Python

R

JavaScript

Stand-alone language

Tableau

Excel

MATLAB

SAS

SPSS Stata

SQL

Alteryx

Other

24. Which of the following areas do your responsibilities cover? Please select all that apply.

Administrative tasks (e.g. scheduling meetings)

Align team goals and objectives

Conduct team meetings

Stakeholder engagement and management

Business intelligence and strategy

Cloud computing

Cybersecurity analysis

Data engineering

Data visualisation

Data warehousing

Feature selection and engineering

Market data analytics

Model deployment

Model development

Model evaluation

Monitoring and maintenance (e.g., data quality, pipelines, compliance)

Reinforcement learning

Scientific publications and conference presentations

Supervised learning

Semi-supervised and active learning

Training and supervision

Treatment of patients

Technical project/program management

Unsupervised learning

Transfer learning

Other

25. Which tasks would you like to perform less of? Please select all that apply.

Administrative tasks (e.g. scheduling meetings)

Align team goals and objectives

Conduct team meetings

Stakeholder engagement and management

Business intelligence and strategy

Cloud computing

Cybersecurity analysis

Data engineering

Data visualisation

Data warehousing

Feature selection and engineering

Market data analytics

Model deployment

Model development

Model evaluation

Monitoring and maintenance (e.g., data quality, pipelines, compliance)

Reinforcement learning

Scientific publications and conference presentations

Supervised learning

Semi-supervised and active Learning

Training and supervision

Treatment of patients

Technical project/program management

Unsupervised learning

Transfer learning

Other

26. Which are your favourite tasks? Please select all that apply.

Administrative tasks (e.g. scheduling meetings)

Align team goals and objectives

Conduct team meetings

Stakeholder engagement and management

Business intelligence and strategy

Cloud computing

Cybersecurity analysis

Data engineering

Data visualisation

Data warehousing

Feature selection and engineering

Market data analytics

Model deployment

Model development

Model evaluation

Monitoring and maintenance (e.g., data quality, pipelines, compliance)

Reinforcement learning

Scientific publications and conference presentations

Supervised learning

Semi-supervised and active Learning

Training and supervision

Treatment of patients

Technical project/program management

Unsupervised learning

Transfer learning

Other

27. How much time do you spend on switching between tasks? I.e., the time between shifting from one task to another. Please estimate a percentage of your entire work schedule since you started working in your current position. I.e., an average across all your tasks and projects.

No need to switch

Less than 5 %

5 - 9 %

10 - 14 %

15 - 19 %

20 - 29 %

30 % and above

28. How much time do you spend on switching between tools (e.g., Excel, R, etc.)?

No need to switch

Less than 5 %

5 - 9 %

10 - 14 %

15 - 19 %

20 - 29 %

30 % and above

29. What kind of code do you usually write?

I don’t write code.

Production code

Research code

Other

30. What are the most useful skills for your work?

Problem-solving

Critical thinking

Time management

Networking

Presentation

Business acumen and strategic thinking

Leadership

Data analysis

Software engineering

Statistical analysis and data modeling

Data visualisation

Databases

Data engineering

Natural language processing (NLP)

Deep learning

Cloud computing

Distributed computing and HPC

Experimentation and A/B testing

Feature engineering

Ensemble learning

Data ethics and privacy

Other

31. How is your performance assessed?

I am not aware how my performance is assessed.

More focused on output (e.g., finances raised, publications) than process.

More focused on process (e.g., time spent on your tasks & helping colleagues) than output.

Other

32. Overall, you are very happy with your current job.

1 (totally disagree)

2

3

4

5 (totally agree)

33. Your users can communicate precisely what they want from the collected and analysed data (e.g. research collaborators, supervisors, team managers, other functions within the organisation, customers).

1 (totally disagree)

2

3

4

5 (totally agree)

35. What could be done to make your work environment more enjoyable and elevate your work? Please select all that apply.

Employee engagement activities — e.g., monthly social gatherings

Transparent policies and practices — e.g., open-door policy

Encouragement of creativity — e.g., focused data challenges, hackathons

Support for mental health — e.g., mental health support services

Flexibility and autonomy — e.g., remote work options

Data sampling procedure — e.g., to improve data quality

Data availability — e.g., fewer missing or delayed data, better data curation

Coding support — e.g., code templates, copilot, pair-coding

Data preparation — e.g., better combining siloed data to enable analysis

Data access — e.g., ICF / CoU checks

Scale — e.g., quicker visualisation of large data sets

Precision — e.g., defined confidence level for the analysis, having clear uncertainty requirements

Use of data outputs

Other

38. Have you filled out similar surveys about your work life and environment?

Yes

No

39. If yes, how much positive impact did those survey’s results have on your work environment?

None

Little impact

Noticeable impact

Significant impact

41. How did you hear about our survey?

My organisation’s internal communications channel (e.g. mailing list, newsletter)

LinkedIn

The Bumblekite website

Recommendations from friends

Other