cswork / libraryOpen practice workspace

Interview guides · Pra Health Sciences

Pra Health Sciences Software Engineer Interview Guide

Pra Health Sciences Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

At Pra Health Sciences (an ICON company), a Software Engineer plays a pivotal role at the intersection of healthcare, data science, and enterprise technology. The engineering team is responsible for developing, optimizing, and maintaining the highly secure, scalable platforms that manage global clinical trial data. Because clinical research directly impacts human health and regulatory approvals, the software you build and maintain must meet exceptional standards of reliability, accuracy, and compliance. Depending on your specific team alignment, your work may focus on building robust enterprise web applications using.NET Core and SQL, or developing specialized data pipelines using SAS and clinical data standards like CDISC (SDTM and ADaM).

This guide is scoped to a Software Engineer candidate at Pra Health Sciences.

Focus areas

  • SAS (Statistical Analysis System)
  • Technical Interviewing
  • SQL

The Pra Health Sciences interview process

Pra Health Sciences candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screening

Initial discussion to align on background, salary expectations, and overall fit.

What to demonstrate

  • Initial discussion to align on background, salary expectations, and overall fit
  • Depth in SAS (Statistical Analysis System)

How to prepare

  • Be able to walk your CV end to end in two minutes, and say why this company specifically.
  • Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.

Automated Technical Assessment

Complete an online aptitude test or specialized technical assessment, such as a SAS test or coding challenge.

What to demonstrate

  • Complete an online aptitude test or specialized technical assessment, such as a SAS test or coding challenge
  • Depth in SAS (Statistical Analysis System)

How to prepare

  • Answer aloud and timed: Describe your experience with SAS Macros. How do you design a macro to automate repetitive clinical data cleaning tasks?
  • Answer aloud and timed: What are some of the mandatory variables required in an SDTM DM (Demographics) domain?

Technical and Managerial Interviews

Meet with engineering leads, managers, and senior leadership to discuss technical depth and behavioral competencies.

What to demonstrate

  • Meet with engineering leads, managers, and senior leadership to discuss technical depth and behavioral competencies
  • Depth in SAS (Statistical Analysis System)

How to prepare

  • Answer aloud and timed: How do you handle missing data or unexpected data types when importing clinical datasets into a validation pipeline?
  • Answer aloud and timed: How do you design and secure a.NET Core Web API to handle sensitive patient data?

Client Sponsor Interview

For FSP roles, a final round interview with a client sponsor to ensure team alignment.

What to demonstrate

  • For FSP roles, a final round interview with a client sponsor to ensure team alignment
  • Depth in SAS (Statistical Analysis System)

How to prepare

  • Answer aloud and timed: Write a SQL query to identify and remove duplicate patient records while preserving the integrity of longitudinal study data.
  • Answer aloud and timed: Explain the concept of dependency injection in.NET and how it improves the testability of your code.

Where candidates lose points

Master the CDISC Specs

Do not rely solely on automated validation tools. Take the time to study the actual SDTM and ADaM implementation guides so you can confidently explain why certain variables are structured the way they are.

During technical interviews, always explain your thought process out loud

Interviewers are often more interested in your structured approach to problem-solving than in your immediate recall of specific syntax rules.

Brush Up on SQL

Regardless of whether you are interviewing for a.NET role or a SAS-heavy clinical programming role, SQL is a core evaluation area. Be prepared to discuss joins, subqueries, and database indexing.

Questions & practice

What are some of the mandatory variables required in an SDTM DM (Demographics) domain?

Medium · Clinical Data & Statistical Programming

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.

Follow-up

  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Archive a resource graph without breaking live references or recursing

Medium · graph traversal · topological order · tenant isolation

Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.

Approach

  1. Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
  2. Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
  3. Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
  4. Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.

Follow-up

  • The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
  • The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?

Identify the heaviest tenants in a five-minute window under memory pressure

Medium · top-k · heavy hitters · streaming

The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.

Approach

  1. Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
  2. Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
  3. State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
  4. Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.

Follow-up

  • The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
  • Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?

Write a SQL query to identify and remove duplicate patient records while preserving the integrity of longitudi

Medium · Enterprise Software Development & Databa

Write a SQL query to identify and remove duplicate patient records while preserving the integrity of longitudinal study data.

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. Handle the rows that do not match: that is usually the actual question.

Follow-up

  • How does the query change if that join becomes one-to-many?
  • What happens to this when the table is ten times larger?

How do you optimize a slow-performing SQL query that is running against a database containing millions of clin

Medium · Enterprise Software Development & Databa

How do you optimize a slow-performing SQL query that is running against a database containing millions of clinical records?

Approach

  1. Name the grain you start from and join outward from it.
  2. Check whether any join is one-to-many before aggregating, or the sums inflate.
  3. Say which index the query would use, and what makes it unusable.
  4. Handle the rows that do not match: that is usually the actual question.

Follow-up

  • How does the query change if that join becomes one-to-many?
  • What happens to this when the table is ten times larger?

Explain the difference between SDTM and ADaM datasets, and describe how variables flow from one to the other.

Medium · Clinical Data & Statistical Programming

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

How do you perform double-programming validation of TFLs (Tables, Figures, and Listings) to ensure regulatory

Medium · Clinical Data & Statistical Programming

How do you perform double-programming validation of TFLs (Tables, Figures, and Listings) to ensure regulatory compliance?

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

How do you design and secure a.NET Core Web API to handle sensitive patient data?

Medium · Enterprise Software Development & Databa

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. State the consistency you need, and where you are willing to be stale.

Follow-up

  • What breaks first when traffic grows ten times?
  • How does this behave when that dependency is down for an hour?

Explain the concept of dependency injection in.NET and how it improves the testability of your code.

Medium · Enterprise Software Development & Databa

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. Work from the requirement backwards to the design.

Follow-up

  • What assumption would you test first?
  • How would you know your answer was wrong?

Read latency spikes on a sixty-second sawtooth

Medium · cache stampede · single-flight · ttl

The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.

Approach

  1. Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
  2. Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
  3. Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
  4. De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.

Follow-up

  • The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
  • How does your answer change if the recompute takes 4 seconds instead of 250 ms?

Suggested practice checklist

Built from the rounds and topics Pra Health Sciences candidates report.

Day 1 — Map the Pra Health Sciences loop

  • Write out the reported sequence: Recruiter Screening, Automated Technical Assessment, Technical and Managerial Interviews, Client Sponsor Interview.
  • For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.

Day 2 — Work SAS (Statistical Analysis System)

  • Spend the session on SAS (Statistical Analysis System), which Pra Health Sciences candidates report being tested on.
  • Write one worked example in SAS (Statistical Analysis System) and time yourself on it.

Deliverable: One timed worked example in SAS (Statistical Analysis System).

Day 3 — Work Technical Interviewing

  • Spend the session on Technical Interviewing, which Pra Health Sciences candidates report being tested on.
  • Write one worked example in Technical Interviewing and time yourself on it.

Deliverable: One timed worked example in Technical Interviewing.

Day 4 — Work SQL

  • Spend the session on SQL, which Pra Health Sciences candidates report being tested on.
  • Write one worked example in SQL and time yourself on it.

Deliverable: One timed worked example in SQL.

Day 5 — Answer out loud: Clinical Data & Statistical Programming

  • Answer aloud, timed: Explain the difference between SDTM and ADaM datasets, and describe how variables flow from one to the other.
  • Answer aloud, timed: How do you perform double-programming validation of TFLs (Tables, Figures, and Listings) to ensure regulatory compliance?

Deliverable: Spoken answers to 2 reported Clinical Data & Statistical Programming question(s), under time.

Day 6 — Answer out loud: Enterprise Software Development & Databases

  • Answer aloud, timed: How do you design and secure a.NET Core Web API to handle sensitive patient data?
  • Answer aloud, timed: Write a SQL query to identify and remove duplicate patient records while preserving the integrity of longitudinal study data.

Deliverable: Spoken answers to 2 reported Enterprise Software Development & Databases question(s), under time.

Day 7 — Answer out loud: Behavioral & Situational Leadership

  • Answer aloud, timed: Describe a time when you had to manage multiple competing deadlines for a critical study submission. How did you prioritize your work?
  • Answer aloud, timed: How do you handle a situation where a peer or senior stakeholder disagrees with your technical approach?

Deliverable: Spoken answers to 2 reported Behavioral & Situational Leadership question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

Describe your experience with SAS Macros. How do you design a macro to automate repetitive clinical data clean

Medium · Clinical Data & Statistical Programming

Describe your experience with SAS Macros. How do you design a macro to automate repetitive clinical data cleaning tasks?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

How do you handle missing data or unexpected data types when importing clinical datasets into a validation pip

Medium · Clinical Data & Statistical Programming

How do you handle missing data or unexpected data types when importing clinical datasets into a validation pipeline?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Describe your experience with modern front-end frameworks like React and TypeScript in building data-dense das

Medium · Enterprise Software Development & Databa

Describe your experience with modern front-end frameworks like React and TypeScript in building data-dense dashboards.

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Describe a time when you had to manage multiple competing deadlines for a critical study submission. How did y

Medium · Behavioral & Situational Leadership

Describe a time when you had to manage multiple competing deadlines for a critical study submission. How did you prioritize your work?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

How do you handle a situation where a peer or senior stakeholder disagrees with your technical approach?

Medium · Behavioral & Situational Leadership

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Explain a scenario where you had to lead a technical study or project. How did you delegate tasks and track pr

Medium · Behavioral & Situational Leadership

Explain a scenario where you had to lead a technical study or project. How did you delegate tasks and track progress?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Tell me about a time you made a mistake in your code that impacted a dataset or system. How did you identify,

Medium · Behavioral & Situational Leadership

Tell me about a time you made a mistake in your code that impacted a dataset or system. How did you identify, report, and resolve the issue?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

How do you maintain a growth mindset when working with legacy technologies or highly rigid regulatory framewor

Medium · Behavioral & Situational Leadership

How do you maintain a growth mindset when working with legacy technologies or highly rigid regulatory frameworks?

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.

Follow-up

  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?