About TetraScience
TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.
The RoleThis role is the CFO's right hand person, and a reliable business partner for the rest of the organization.
There are two aspects to the role. The first is ownership of the TetraScience financial model, the company's single source of truth for its annual operating plan, quarterly forecasts, scenarios, headcount and cash, along with the cycles that run on it: the monthly flash, the month-end close board reporting, leadership team reporting, variance analyses, and the weekly cash forecast. The second is managing the information flow around the leadership team: shared agendas, diving into key metrics, capturing decisions, and bringing closure to strategic initiatives along with the CFO.
What you will doThe financial model
- Own the TetraScience financial model end-to-end. The model is internally built and operated through an AI assistant layer that needs to be maintained and augmented as needed. The FP&A Director will use the financial model to explain results and forecast the future. We are hiring the person who does that part, and who keeps automating the rest.
- Run the monthly flash and month-end close process post-Accounting close.
- Own the company’s Plan, Actual, Variance, Root Cause Analysis, Remediation (PAVRR) process for financial data.
- Support global resource planning. Reconcile modeled headcount against actuals, and maintain and keep our employee roster, vendor, and expense detail current.
- Manage the company’s financial planning cycle on a quarterly basis. Collecting input from TetraScience’s executive team and sharing variance reporting on a monthly basis.
The leadership operating cadence
- Coordinate the agenda for the TetraScience Leadership Team (TLT) meeting, the bi-weekly extended leadership team meeting: solicit topics, build and publish the agenda and pre-reads, and circulate materials ahead of time.
- Collect inputs that feed TLT metric reporting from across the business, including pipeline and ARR/ACV, hiring metrics for critical roles, delivery and customer health, functional KPIs, and normalize them into one consistent pack.
- Prepare the CFO for the forums he does not run: briefing notes, the questions worth asking, and the follow-ups owed.
G&A business partnership
- Act as the finance approver and partner for HR, Recruiting, IT and Marketing: requisitions, planned and incremental headcount, offer budgets, and comp, bonus and salary adjustments.
- Approve and track contractor engagements and extensions.
- Own the vendor, SaaS, tooling and marketing budget, covering ERP, recruiting and sourcing tools, background checks, new SaaS and AI tools, laptop and IT spend, and events, conferences and swag, including over-budget escalations.
- Partner with Sales Ops on commission plan tables and calculations.
- Produce and publish budget-versus-actual P&Ls for G&A, R&D and Delivery.
Reporting and analysis
- Weekly cash forecast and weekly pipeline snapshot.
- Monthly KPI reporting: ARR and ACV, NRR and GRR, bookings coverage, CAC payback, burn multiple, ARR per FTE, turnover and time to hire.
- Lender and bank reporting packages, investor reporting, and data-room and diligence support during financing processes.
Requirements Key Competencies
- You have been an FP&A analyst and you were good at it. You can still build the model yourself and you want to. What has changed is that you now get asked the question before the analysis rather than after, and you are comfortable there.
- You are the person who arrives at meetings having read everything, having noticed the two numbers that disagree, and having formed a view. You bring problems you have already worked on, with a recommendation on solutions.
- You are fluent with AI tooling, and you have built things with it. You will be operating a financial model through an AI assistant and writing the workflows that make next month's work smaller than this month's.
- Clear writing. A large share of this job is the one paragraph that makes a number make sense to someone who does not work in finance.
- Sound judgment with confidential material: compensation, equity, headcount plans and financing.
- Bachelor's degree in Finance, Accounting, Economics or a comparable quantitative field. A CFA, CPA or MBA is welcome, and is not a substitute for the modeling bar above.
- 7 to 10 years in FP&A, corporate finance, investment banking or consulting, including at least 3 years inside a high-growth B2B technology business.
- Expert financial modeling in Excel or Google Sheets: three-statement, driver-based, scenario and cohort models built from scratch. You should be able to walk us through one you own.
- Working command of SaaS metrics, including ARR and ACV and the difference between them, NRR and GRR, bookings coverage, CAC payback, burn multiple and magic number, and of what moves each one.
- Demonstrated ownership of an executive or board-level operating cadence: agenda, pre-reads, decision capture, follow-through.
- Hands-on AI fluency. You have built or materially extended a working process with Claude, ChatGPT or comparable tooling, and you can describe what you built, where it broke, and how you check its output.
- Reading fluency in NetSuite or a comparable ERP, and in Salesforce. BI tooling such as Looker, Tableau or Sigma, and SQL, are useful but not required.
- Willingness to travel as needed.
The salary range for this position is $200,000 - $250,000. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.
Benefits
- 100% employer-paid benefits for all eligible employees and immediate family members
- Unlimited paid time off (PTO)
- 401K
- Company paid Life Insurance, LTD/STD
- A culture of continuous improvement where you can grow your career and get coaching
We are not currently providing visa sponsorship for this position
Skills Required
- Bachelor's degree in Finance, Accounting, Economics, or a comparable quantitative field
- 7 to 10 years of experience in FP&A, corporate finance, investment banking, or consulting
- At least 3 years of experience within a high-growth B2B technology business
- Expert financial modeling skills in Excel or Google Sheets, including three-statement, driver-based, scenario, and cohort models
- Working knowledge of SaaS metrics including ARR, ACV, NRR, GRR, bookings coverage, CAC payback, burn multiple, and magic number
- Experience owning an executive- or board-level operating cadence, including agendas, pre-reads, decision capture, and follow-through
- Hands-on experience building or materially extending processes with Claude, ChatGPT, or comparable AI tools
- Ability to read and use NetSuite or a comparable ERP and Salesforce
- Clear written communication and sound judgment when handling confidential compensation, equity, headcount, and financing information
- CFA, CPA, or MBA
- Experience with BI tools such as Looker, Tableau, or Sigma
- SQL experience
- Willingness to travel as needed
What We Do
Biopharma R&D runs on data trapped in silos. Every instrument, ELN, and LIMS writes results in its own format, so most of what a scientist learns in one experiment never reaches the next. That's a big reason drug development costs keep climbing even as computing power gets cheaper. TetraScience builds Tetra OS, the operating system for scientific intelligence. It sits above and alongside a company's existing instruments, ELNs, and LIMS, works across any vendor, and turns raw scientific data into structured, AI-ready intelligence. Four components make it work. The Scientific Data Foundry ingests data from any source and converts it into governed, machine-readable data at scale. The Scientific Use Case Factory turns one-off workflows into reusable, validated ones deployed across sites. Tetra AI reasons and orchestrates on top of that foundation, grounded in real data instead of guessing. Sciborg teams, our embedded scientist-engineers, work inside customer organizations to get all of it adopted, not just installed. These parts compound. Better data makes workflows faster to build. Workflows generate better data. The result is intelligence that gets more valuable with use instead of resetting on every new project. Customers include Takeda, Bayer, Regeneron, Roche and and AstraZeneca, alongside partners like NVIDIA, Databricks, and Thermo Fisher Scientific. One top-20 pharma customer connected over 1,000 instruments, processed a petabyte of data in a year, and cut 20,000 hours of administrative work. Founded by Patrick Grady and Spin Wang, headquartered in Boston with a European base in Basel. Mission: radically improve and extend human life.
Why Work With Us
We're building the operating system underneath scientific R&D, not another point tool. Work touches real drug development at Takeda, Bayer, and Novartis. Every employee sees the same financials the board sees. We hire people who reason from first principles and run at hard problems.
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