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Software Engineers, Here’s How To Land Your Dream Job at Datavant

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Datavant
June 24, 2021

Datavant, a 4 year old startup, has an extremely high bar when we interview candidates. By the numbers, we make an offer to less than 1% of all applicants, yet the criteria we assess for are remarkably straightforward, and preparing for an interview at Datavant should not be difficult if you share our values, are smart, and get things done.

What do we look for?

We look for three traits at Datavant, each with a specific meaning in our process:

  1. Nice (do we have shared values?)
  2. Smart
  3. Get Things Done

Over the past 10 years I’ve interviewed hundreds of candidates for engineering, product, design, R&D, and related tech roles. Interviewing is a unique skill, and regardless of your experience interviewing, it’s impossible for a hiring manager to get to the right decision without a clear definition of the ideal candidate. Furthermore, without clear and objective criteria, hiring decisions become steeped with unconscious bias. That’s why the first step in hiring well is defining excellence.

Datavant is an olympic gold medal sports team, and we want to hire people who will add to our team and help us get to our ambitious goal of connecting the world’s health data that much faster!

Values

Why do we look for it?

We’re very intentional about our culture at Datavant, and the foundation of culture is values; that’s why the first thing we look for in a candidate is shared values.

What is it?

You can see our careers page for an exhaustive list of our values, but there are two that really define Datavant for me:

  • “More Responsibility, Fewer Rules” and
  • “Feedback is a Gift.”

More Responsibility, Fewer Rules is both the result of and the foundation for a culture of trust that ultimately stems from hiring a highly talented, high performing, self-motivated team. When we get excited about “an excellent engineering candidate” it’s someone we can trust to work hard (We Work Hard) and get things done (Perfect is Good, Done is Better) in a way we’re proud of (Always Pass The “Loved One Test”). This comes out in an interview when a candidate demonstrates the ability to execute amidst uncertainty, make decisions, gather context, feedback, and inputs from others, establish alignment with stakeholders, and ultimately see projects through to completion. On the flip side, if you’re the type of person who thrives in a highly structured environment where tasks are clearly defined and you always have all the information you need, then Datavant is probably not the right place for you.

The second Datavant value that really shapes our culture, in my opinion, is “Feedback is a Gift.” We believe that the most successful engineers ask a lot of questions, they seek out and give high quality feedback to their peers and managers on a regular basis, and they tackle challenges with a growth mindset. Datavant does well on many dimensions that are important to candidates, but we’re seeking to be truly best in the world on one dimension: personal growth. The foundation of growth and learning is feedback, and our focus on feedback leads to lots of internal promotions (We Grow Leaders) and engineers in positions where they can Play To Their Strengths. Engineers that are successful at Datavant are highly intelligent and ambitious, but perhaps more importantly, they’re curious, open-minded, and inquisitive.

How do we assess it?

One way that we test for shared values is through our technical phone screen. While we don’t typically practice pair programming in our daily work at Datavant, we do use it to assess candidates. We find that our pair programming exercise tells us a lot about how a candidate receives instructions, questions assumptions, and responds to feedback. Furthermore, this highly structured pair coding interview, allows you to show your knowledge of data structures and your ability to communicate with another engineer. Lastly, and perhaps most importantly, Datavant will never hire jerks, brilliant ones or otherwise, and this collaborative exercise rapidly exposes jerks so we can get them out of our hiring process.

Our values are intentionally aspirational, and while we’re each getting better every day, one of the most powerful ways we can live our values is by hiring people that share them.

Smart

Why do we look for it?

Datavant aspires to be the best place in the world for engineers optimizing for personal growth. The flip side of that is that we look for extremely high potential, high aptitude, growth oriented candidates.

What is it?

We seek out candidates that are:

  1. Exceptionally intelligent
  2. Insatiably curious
  3. Outstanding communicators

We define outstanding communication along four dimensions:

  • Mindset — Do they push out information proactively or wait for you to pull the info in?
  • Structure
  • Do they dissect the main topic into comprehensive arguments?
  • Can I understand the ‘gist’ of what they’re saying?
  • Do they get their point across the first time or do they need to repeat themselves?
  • Comprehension — Can they understand me? Do they demonstrate attentive listening?

A “good communicator” does well on multiple dimensions. To be successful as an engineer at Datavant, a candidate does not need to excel at all of the above, but their communication needs to be effective enough for them to engage in a team, understand priorities and projects, share updates efficiently, and support the learning/growth of other team members. Effective communication is even more essential in our relatively new remote first, largely asynchronous environment.

Previous engineering experience and existing engineering skills are also important for every new Datavant engineer, and we assess for excellence in engineering using the same performance rubric as we use for internal performance reviews, however, we focus much more on a candidate’s problem solving skills and their ability to communicate their ideas effectively, than prior tech stack experience.

How do we assess it?

Datavant is assessing intelligence, curiosity, and communication at every step of the interview process. Does the candidate catch on quickly and learn throughout the interview? Do they ask good questions with thoughtful follow ups? Do they share relevant details when answering questions without getting lost in the weeds?

While being “smart” is a subjective concept that isn’t easily measured, we believe that the Datavant definition of “smart” results in a highly talent dense team where even our strongest team members learn from their colleagues every day.

Get Things Done

Why do we look for it?

Datavant is a hyper growth company, and our engineers create value by getting things done. This might sound trite, but at Datavant we believe in hustle as a strategy. While there’s certainly a place for intellectual discovery, the engineering team at Datavant exists to build products that connect the world’s health data and by doing so, improve patient outcomes. Oftentimes, those problems have deep technical complexities that require thoughtful planning and design, and we value doing that work well, but at the end of the day, Datavant engineers deliver value when they write high quality production code and ship new features and products to customers.

What is it?

Getting things done at Datavant means identifying problems and creating solutions; sometimes that looks like writing code, but for experienced Datavant engineers, that more often looks like spending time to guide, mentor, and teach new engineers, empowering them to get things done.

How do we assess it?

In order to gauge a candidate’s “GTD’’ there is one question I ask every candidate I interview, “Tell me about a project you’re particularly proud of?” This doesn’t necessarily have to be a huge win or a particularly complex project, but we want to know that candidates have a track record of execution and value creation. Great engineering projects typically standout because the candidate:

  1. Took an ambiguous business goal and turned it into an actionable technical plan
  2. Executed on and/or lead a team to execute on the technical plan
  3. Took the project over the finish line; pushed the code to production; delivered real value to users

An ability to get things done might sound like a trivial expectation for a candidate, but in my experience, most people, even very smart ones, procrastinate, tackle the easy tasks first, and avoid the high value high difficulty tasks that we’re looking to get done. Mark Twain famously said, “If you have to eat a frog, eat it first thing in the morning. If you have to eat two frogs, eat the bigger one first.” In other words, “Do it now.” We’re looking for engineers that get up every day and eat the frog.

Join us

We’re not trying to fit every candidate; we’re trying to be the absolute best opportunity in the world for a small subset of candidates. If this sounds like you or someone you know, come join us; we’re focused on the vision of connecting the world’s health data to improve patient outcomes, and we’re hiring!

Spotlight on AnalyticsIQ: Privacy Leadership in State De-Identification

AnalyticsIQ, a marketing data and analytics company, recently adopted Datavant’s state de-identification process to enhance the privacy of its SDOH datasets. By undergoing this privacy analysis prior to linking its data with other datasets, AnalyticsIQ has taken an extra step that could contribute to a more efficient Expert Determination (which is required when its data is linked with others in Datavant’s ecosystem).

AnalyticsIQ’s decision to adopt state de-identification standards underscores the importance of privacy in the data ecosystem. By addressing privacy challenges head-on, AnalyticsIQ and similar partners are poised to lead clinical research forward, providing datasets that are not only compliant with privacy requirements, but also ready for seamless integration into larger datasets.

"Stakeholders across the industry are seeking swift, secure access to high-quality, privacy-compliant SDOH data to drive efficiencies and improve patient outcomes,” says Christine Lee, head of health strategy and partnerships at AnalyticsIQ. 

“By collaborating with Datavant to proactively perform state de-identification and Expert Determination on our consumer dataset, we help minimize potentially time-consuming steps upfront and enable partners to leverage actionable insights when they need them most. This approach underscores our commitment to supporting healthcare innovation while upholding the highest standards of privacy and compliance."

Building Trust in Privacy-Preserving Data Ecosystems

As the regulatory landscape continues to evolve, Datavant’s state de-identification product offers an innovative tool for privacy officers and data custodians alike. By addressing both state-specific and HIPAA requirements, companies can stay ahead of regulatory demands and build trust across data partners and end-users. For life sciences organizations, this can lead to faster, more reliable access to the datasets they need to drive research and innovation while supporting high privacy standards.

As life sciences companies increasingly rely on SDOH data to drive insights, the need for privacy-preserving solutions grows. Data ecosystems like Datavant’s, which link real-world datasets while safeguarding privacy, are critical to driving innovation in healthcare. By integrating state de-identified SDOH data, life sciences can gain a more comprehensive view of patient populations, uncover social factors that impact health outcomes, and ultimately guide clinical research that improves health. 

The Power of SDOH Data with Providers and Payers to Close Gaps in Care

Both payers and providers are increasingly utilizing SDOH data to enhance care delivery and improve health equity. By incorporating SDOH data into their strategies, both groups aim to deliver more personalized care, address disparities, and better understand the social factors affecting patient outcomes.

Payers Deploy Targeted Care Using SDOH Data

Payers increasingly leverage SDOH data to meet health equity requirements and enhance care delivery:

  • Tailored Member Programs: Payers develop specialized initiatives like nutrition delivery services and transportation to and from medical appointments.
  • Identifying Care Gaps: SDOH data helps payers identify gaps in care for underserved communities, enabling strategic in-home assessments and interventions.
  • Future Risk Adjustment Models: The Centers for Medicare & Medicaid Services (CMS) plans to incorporate SDOH-related Z codes into risk adjustment models, recognizing the significance of SDOH data in assessing healthcare needs.

Payers’ consideration of SDOH underscores their commitment to improving health equity, delivering targeted care, and addressing disparities for vulnerable populations.

Example: CDPHP supports physical and mental wellbeing with non-medical assistance

Capital District Physicians’ Health Plan (CDPHP) incorporated SDOH, partnering with Papa, to combat loneliness and isolation in older adults, families, and other vulnerable populations. CDPHP aimed to address:

  • Social isolation
  • Loneliness
  • Transportation barriers
  • Gaps in care

By integrating SDOH data, CDPHP enhanced their services to deliver comprehensive care for its Medicare Advantage members.

Providers Optimize Value-Based Care Using SDOH Data

Value-based care organizations face challenges in fully understanding their patient panels. SDOH data significantly assists providers to address these challenges and improve patient care. Here are some examples of how:

  • Onboard Patients Into Care Programs: Providers use SDOH data to identify patients who require additional support and connect them with appropriate resources.
  • Stratify Patients by Risk: SDOH data combined with clinical information identifies high-risk patients, enabling targeted interventions and resource allocation.
  • Manage Transition of Care: SDOH data informs post-discharge plans, considering social factors to support smoother transitions and reduce readmissions.

By leveraging SDOH data, providers gain a more comprehensive understanding of their patient population, leading to more targeted and personalized care interventions.

While accessing SDOH data offers significant advantages, challenges can arise from:

  • Lack of Interoperability and Uniformity: Data exists in fragmented sources like electronic health records (EHRs), public health databases, social service systems, and proprietary databases. Integrating and securing data while ensuring data integrity and confidentiality can be complex, resource-intensive and risky.
  • Lag in Payer Claims Data: Payers can take weeks or months to release claims data. This delays informed decision-making, care improvement, analysis, and performance evaluation.
  • Incomplete Data Sets in Health Information Exchanges (HIEs): Not all healthcare providers or organizations participate in HIEs. This reduces the available data pool. Moreover, varying data sharing policies result in data gaps or inconsistencies.

To overcome these challenges, providers must have robust data integration strategies, standardization efforts, and access to health data ecosystems to ensure comprehensive and timely access to SDOH data.

SDOH data holds immense potential in transforming healthcare and addressing health disparities. 

With Datavant, healthcare organizations are securely accessing SDOH data, and further enhancing the efficiency of their datasets through state de-identification capabilities - empowering stakeholders across the industry to make data-driven decisions that drive care forward.

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