Bioinformatics Customer Success Specialist

About DNAstack

At DNAstack , our mission is to power precision medicine by building software that breaks down barriers to responsible biomedical data sharing, discovery, and analysis. We build cutting-edge software and industry standards to help researchers and clinicians analyze sequencing data and make faster, more accurate diagnoses. Our platform supports national and international networks tackling rare disease, cancer, infectious disease, and more.

We’re a nimble, cross-functional team of scientists, engineers, designers, and product thinkers working at the intersection of genomics, software, and cloud technologies. Our mission is ambitious, and so is our team.

The Role

The Bioinformatics Customer Success Specialist makes sure every customer gets accurate, timely, and dependable results from the DNAstack platform. You are the technical owner of the customer experience after go-live: the first responder when a run fails, the person who confirms a result is right before it ships, and the voice that brings customer pain points back to engineering and product.

This is a growth-oriented role for an M.S.-level bioinformatician who enjoys both the science and the people. You will start on the front line of our operations: resolving support tickets, monitoring production pipelines across AWS and GCP, running and validating sample batches, and preparing custom deliverables for partners. That work gives you an intimate view of our architecture and of what customers actually need.

As your expertise grows, you will move from fixing issues to preventing them. You will build quality checks and regression tests, benchmark new tools against reference standards, maintain pipeline dependencies, and help set the reliability standards that our clinical and research customers depend on.

What You’ll Do

1. Customer Support and Issue Resolution

Serve as the primary technical point of contact for customer support tickets, partner inquiries, and data delivery requests.

Triage, diagnose, and resolve failed secondary and tertiary pipeline runs, annotation and sorting bugs, and cloud permission issues within agreed response times.

Lead root-cause investigations into missing variants, control sample mismatches (e.g., commercial reference controls), and runtime bottlenecks, and communicate findings clearly to customers.

Turn recurring issues into knowledge-base articles, runbooks, and FAQs so customers and teammates can self-serve.

2. Platform Quality and Reliability

Monitor production workflows and dataset deployments across GCP and AWS, catching failures and performance drift before customers notice.

Define and run quality-control checks on pipeline inputs and outputs, including sample identity, coverage, and variant-level QC metrics.

Run regression and validation tests on new pipeline and platform releases using reference materials (e.g., GIAB) before they reach customers.

Estimate and track workflow compute costs across cloud platforms, giving internal teams and customers realistic cost ranges for workflows and versions and informing selection of preferred cloud when onboarding new customers.

Document incidents with clear root cause, impact, and prevention steps, and track fixes through to completion with engineering.

Maintain and upgrade pipeline dependencies (e.g., Samtools, GATK, AnnotSV within WDL) with full re-validation.

3. Customer Onboarding and Data Operations

Onboard new customers: validate target capture files (BED), metadata sheets, and sample identifiers before first execution.

Create and maintain onboarding guides, runbooks, and FAQs for new customers, and own their success from first login through processing their samples at scale.

Submit, track, and verify routine sample runs and re-analyses across customer accounts.

Re-index, reload, and verify dataset nodes across deployment environments after updates.

4. Custom Deliverables and Customer Value

Generate customized data subsets, including read-supporting BAM slices, collection-level VCFs, and targeted TSV extracts.

Format and QC structural variant (SV), short tandem repeat (STR), and methylation outputs for partner handoffs.

Partner with Business Development on demo datasets, proofs of concept, and compute cost estimates for prospective customers.

5. Voice of the Customer (Growth)

Bring structured customer feedback to product and engineering to shape the roadmap and reliability priorities.

Benchmark variant callers and pipeline parameters to inform recommendations to customers.

Partner with the Staff Bioinformatician on exploratory features (e.g., new SV merging strategies) and join our internal bioinformatics journal club.

What We’re Looking For

Master's degree in computational biology, bioinformatics, biostatistics, computer science, or equivalent experience.

1–3 years of professional experience in an industry biotech, diagnostic, or clinical bioinformatics role, ideally customer- or partner-facing.

Exceptional written and verbal communication; able to explain complex technical issues to non-computational stakeholders.

Structured, methodical approach to troubleshooting and root-cause analysis.

Hands-on experience running and debugging NGS and -omics data processing pipelines.

Working knowledge of common genomics file types (FASTQ, BAM/CRAM, VCF, BED) and analysis tools.

Proficiency in Python (preferred), R, or Java, and a solid grasp of shell scripting and the command line.

Strong attention to detail and a sense of ownership for data quality.

Background in biology or genetics with proven critical thinking and research skills.

Nice to Have

Experience with workflow languages (e.g., WDL, CWL, Nextflow, Snakemake) and containers (Docker, Singularity).

Experience with cloud computing (GCP, AWS, Azure) or HPC environments, including monitoring and logging tools.

Experience with automated testing or CI/CD for bioinformatics pipelines.

Familiarity with quality systems or regulated environments (e.g., CAP/CLIA, ISO 13485) and validation documentation.

Experience with ticketing or customer success tools (e.g., Jira Service Management, Zendesk, Intercom).

Long-read sequencing experience (e.g., PacBio HiFi), including SV, STR, and methylation analysis.

Strong statistical skills and experience building effective data visualizations.

Wet lab genomics experience (e.g., library preparation, protocol design).

Experience using modern AI tools ( e.g. Claude Code)

Why This Role Is Exciting

Impact at scale : Your work will directly influence tools used by national and international genomics networks.

Build something new : Shape a core function of the company from a small, senior team into a scalable, sustainable group.

Cross-disciplinary collaboration : Work side by side with engineers, product managers, and scientists to turn bioinformatics into real-world solutions.

Mission-driven : Contribute to solving rare disease, cancer, and infectious disease challenges by enabling precision medicine.

Team culture: Enjoy a flexible, remote-friendly team culture along with a competitive salary, benefits, and employee stock option program.

Where You'll Work

This role offers the flexibility of remote work, with the option to work in person from our Toronto office. This arrangement supports your needs and promotes a healthy work–life balance.

Eligibility

To be considered for this position, you must be eligible to work in Canada.

Benefits

Remote friendly, with flexible hours and the opportunity to work on-site at our Toronto office

Comprehensive health benefits: medical, dental and vision coverage for you and your dependents

Three weeks vacation

Unlimited sick days

Maternity and parental leave top-up programs

One-time remote office set-up stipend

Career development and learning support

Opportunity to participate in DNAstack's Employee Stock Option Program

Opportun