Senior Director, Data Science & Engineering
Unite Us · United States · 1 mo ago
RemoteRemoteEngineering$225k–$275k/yrFull-time
We need to output HTML fragment with sections: About the role (already present), Responsibilities (What You'll Do), Requirements (You’re a great fit for this role if: list), Benefits, Pay, Schedule? The posting includes pay range and remote info, schedule maybe remote, travel 5-10%. Should we include Schedule? The posting mentions remote, US based, preference for ET/CT time zones, may require 5-10% travel. That's schedule info (remote, travel). So we can include Schedule section with that info. Benefits: list of benefits. Pay: target pay range.
We must not repeat job title as heading. Use for each section heading.
We need to preserve all substantive info, not invent. Remove boilerplate like mission, environmental job requirements? Actually environmental job requirements includes remote, travel, pay range, benefits. We'll keep those.
We need to exclude mission, EEO, etc.
We need to format lists with
for each section heading.
We need to preserve all substantive info, not invent. Remove boilerplate like mission, environmental job requirements? Actually environmental job requirements includes remote, travel, pay range, benefits. We'll keep those.
We need to exclude mission, EEO, etc.
We need to format lists with - . For prose use
.
We need to include sections only when there is real specific content.
Let's extract:
About the Role: paragraph(s). We'll put as
.
Responsibilities: "What You'll Do:" then bullet points under subheadings? The posting has headings within What You'll Do: Team Leadership & People Development, Technical Strategy & Architecture, Roadmap & Execution, Cross-Functional Collaboration, Hiring & Talent. Those are subheadings but we are only to use
for section headings (About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should not create additional headings; we can keep the content under Responsibilities as a list or paragraphs. Probably we can keep the bullet points as list items, preserving the subheadings as bold? But we cannot add extra headings; we can embed the subheadings as strong text inside
- . That's okay.
Thus Responsibilities section:
Responsibilities
then maybe a with each major area as - containing the description.
We need to capture all bullet points under each area.
Let's list them:
Team Leadership & People Development:
- Lead, mentor, and grow a group of engineering and data science managers, and, through them, their teams of data engineers, analysts, and data scientists.
- Set and hold a high bar for technical talent across the data organization; define career ladders and growth paths for managers and senior ICs.
- Manage team-of-teams performance from both a technical and personnel perspective, including performance calibration and succession planning.
Technical Strategy & Architecture:
- Own the technical strategy and roadmap for the data platform and Insights product line, partnering with Product and Engineering leadership to balance innovation with business priorities.
- Establish and enforce engineering and analytical best practices across teams: code review standards, testing, CI/CD, model validation, monitoring, and incident response.
- Guide architecture decisions across data pipelines, the data lakehouse/warehouse, and applied data science/ML workflows, validating designs in AWS.
- Drive consistency and efficiency in data pipeline implementations and cross-product data/testing/deployment standards.
Roadmap & Execution:
- Own creation and execution of the group's multi-quarter roadmap, sequencing initiatives and aligning timelines with business goals.
- Manage capacity planning and prioritization across multiple teams, resolving contention and dynamically responding to shifting priorities.
- Identify and mitigate delivery risks before they become roadblocks, escalating judiciously and without damaging relationships.
Cross-Functional Collaboration:
- Act as a thought partner to Product, UX, and Analytics counterparts on the Insights roadmap and broader data strategy.
- Represent the data organization to senior leadership and executive stakeholders, translating high-level initiatives into actionable team goals and reporting on key performance indicators.
- Partner with Application Engineers, Product Managers, and other engineering teams to translate business requirements into scalable pipeline and platform designs.
Hiring & Talent:
- Identify, recruit, and hire the best engineering and data science talent for the organization, including manager-level hires.
Now Requirements: "You’re a great fit for this role if:" then bullet list.
List:
- 8+ years of progressive experience across software engineering, data engineering, and/or data science, including experience leading multi-team initiatives.
- 5+ years of people management experience, including experience managing managers or senior individual contributors.
- At least 2+ years in healthcare, digital health, or health technology, using Agile delivery methodologies.
- Experience building complex software and data products within healthcare and/or government settings, with demonstrable success.
- Experience with data pipeline architectures (e.g., Apache Airflow), complex software systems, large-scale databases and/or cloud data warehousing platforms (e.g., Snowflake, Redshift, Databricks), including performance tuning and cost management.
- Working knowledge of applied data science/ML workflows and how they integrate with production data platforms.
- Strong knowledge of programming languages and paradigms, including SQL and Python.
- Experience operating in a regulated or compliance-sensitive data environment.
- Experience with Cloud infrastructure (AWS preferred) technologies.
- Excellent verbal and written communication skills; ability to represent technical strategy to non-technical executive audiences.
- BS/BA degree in Computer Science, Data Science, or a related field, or equivalent experience.
We could also include Qualifications/Skills but we can combine into Requirements. The instruction says use headings like Requirements, Qualifications, Skills. We have content for Requirements. Could also separate Skills but not needed.
Benefits: list from "Benefits provided by Unite Us:" then bullet points.
List:
- Medical, Dental, and Vision: We offer insurance to team members and eligible partners and dependents, including unlimited virtual mental health and acute medical visits.
- Wellness: Mental health benefits, such as the Employee Assistance Program (EAP) and wellness platform subscription, are available to all team members.
- Flexible Time Off: Take what you need, including volunteer days and mental health days. We also offer 14 paid, company-wide holidays.
- Paid Parental Leave: Adoptive parents are included.
- Employee Resource Groups: Join our ERGs to connect and engage with colleagues, like Military Veterans
- Spending Accounts: We offer tax-advantaged health savings accounts (HSAs), flexible spending accounts (FSAs), and commuter benefits.
- 401(k) + Employer Match: Enjoy matching, immediate vesting and financial wellness resources
- Additional Benefits: Life and AD&D - a company paid benefit, with the option to purchase additional coverage for yourself and your dependents
- Disability Coverage
- Accident Insurance
- Pet Insurance
- As part of this work at home job, we will provide you with all the necessary equipment to perform your duties, including a computer, mouse, keyboard as well as other items on our approved list of WFH supplies.
We need to keep each as list items.
Pay: "The target pay range for this role is: $225,000-$275,000. This salary range represents our target hiring range for this role. The proposed salary will be dependent on the candidate's skills, experience, and competencies, as well as location."
Schedule: remote, US based, preference for ET/CT time zones, may require 5-10% travel.
We'll put Schedule section with that.
Now produce HTML fragment.
We must not include or . Just the sections.
Let's craft:
About the Role
The Senior Director, Data Science & Engineering owns the technical strategy, architecture, and delivery of Unite Us' data platform and Insights product line, spanning both data engineering and data science disciplines. You will manage a team of managers and senior individual contributors, ensuring the group's roadmap balances technical soundness, business impact, and long-term platform scalability. You will partner closely with Product, Engineering, and Analytics leadership to translate company strategy into a coherent multi-team roadmap, while remaining close enough to the technical details to make sound architectural tradeoffs, evaluate build-vs-buy decisions, and unblock complex cross-team dependencies. You have deep knowledge of modern software & data platforms (cloud infrastructure, complex software systems, data pipelines, data warehousing, and applied data science/ML) and healthcare or social-care data standards, and you use that knowledge to raise the bar for engineering and analytical rigor across the group. You will build, mentor, and manage a group of engineering and data science managers, define what a high-performing team looks like, and hold the organization accountable to that bar. You are comfortable operating with significant autonomy, managing up and across the organization, and representing the data organization to executive stakeholders.
Responsibilities
- Team Leadership & People Development
- Lead, mentor, and grow a group of engineering and data science managers, and, through them, their teams of data engineers, analysts, and data scientists.
- Set and hold a high bar for technical talent across the data organization; define career ladders and growth paths for managers and senior ICs.
- Manage team-of-teams performance from both a technical and personnel perspective, including performance calibration and succession planning.
- Technical Strategy & Architecture
- Own the technical strategy and roadmap for the data platform and Insights product line, partnering with Product and Engineering leadership to balance innovation with business priorities.
- Establish and enforce engineering and analytical best practices across teams: code review standards, testing, CI/CD, model validation, monitoring, and incident response.
- Guide architecture decisions across data pipelines, the data lakehouse/warehouse, and applied data science/ML workflows, validating designs in AWS.
- Drive consistency and efficiency in data pipeline implementations and cross-product data/testing/deployment standards.
- Roadmap & Execution
- Own creation and execution of the group's multi-quarter roadmap, sequencing initiatives and aligning timelines with business goals.
- Manage capacity planning and prioritization across multiple teams, resolving contention and dynamically responding to shifting priorities.
- Identify and mitigate delivery risks before they become roadblocks, escalating judiciously and without damaging relationships.
- Cross-Functional Collaboration
- Act as a thought partner to Product, UX, and Analytics counterparts on the Insights roadmap and broader data strategy.
- Represent the data organization to senior leadership and executive stakeholders, translating high-level initiatives into actionable team goals and reporting on key performance indicators.
- Partner with Application Engineers, Product Managers, and other engineering teams to translate business requirements into scalable pipeline and platform designs.
- Hiring & Talent
- Identify, recruit, and hire the best engineering and data science talent for the organization, including manager-level hires.
But note: we used nested inside - . That's okay but might be considered extra structure. The instruction: Use
- for any list of duties/requirements/benefits. It didn't forbid nested lists. However we could flatten: each responsibility area as a
- with the subheading as strong text and then the bullet points as separate
- ? But that would lose grouping. Probably nested is fine.
Alternatively we could make each area a
- and then inside that
- we have a
for the points. That's acceptable.
Now Requirements:
Requirements
- 8+ years of progressive experience across software engineering, data engineering, and/or data science, including experience leading multi-team initiatives.
- 5+ years of people management experience, including experience managing managers or senior individual contributors.
- At least 2+ years in healthcare, digital health, or health technology, using Agile delivery methodologies.
- Experience building complex software and data products within healthcare and/or government settings, with demonstrable success.
- Experience with data pipeline architectures (
. We need to include sections only when there is real specific content. Let's extract: About the Role: paragraph(s). We'll put as
. Responsibilities: "What You'll Do:" then bullet points under subheadings? The posting has headings within What You'll Do: Team Leadership & People Development, Technical Strategy & Architecture, Roadmap & Execution, Cross-Functional Collaboration, Hiring & Talent. Those are subheadings but we are only to use
for section headings (About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should not create additional headings; we can keep the content under Responsibilities as a list or paragraphs. Probably we can keep the bullet points as list items, preserving the subheadings as bold? But we cannot add extra headings; we can embed the subheadings as strong text inside
Responsibilities
then maybe a- with each major area as
- containing the description.
We need to capture all bullet points under each area.
Let's list them:
Team Leadership & People Development:
- Lead, mentor, and grow a group of engineering and data science managers, and, through them, their teams of data engineers, analysts, and data scientists.
- Set and hold a high bar for technical talent across the data organization; define career ladders and growth paths for managers and senior ICs.
- Manage team-of-teams performance from both a technical and personnel perspective, including performance calibration and succession planning.
Technical Strategy & Architecture:
- Own the technical strategy and roadmap for the data platform and Insights product line, partnering with Product and Engineering leadership to balance innovation with business priorities.
- Establish and enforce engineering and analytical best practices across teams: code review standards, testing, CI/CD, model validation, monitoring, and incident response.
- Guide architecture decisions across data pipelines, the data lakehouse/warehouse, and applied data science/ML workflows, validating designs in AWS.
- Drive consistency and efficiency in data pipeline implementations and cross-product data/testing/deployment standards.
Roadmap & Execution:
- Own creation and execution of the group's multi-quarter roadmap, sequencing initiatives and aligning timelines with business goals.
- Manage capacity planning and prioritization across multiple teams, resolving contention and dynamically responding to shifting priorities.
- Identify and mitigate delivery risks before they become roadblocks, escalating judiciously and without damaging relationships.
Cross-Functional Collaboration:
- Act as a thought partner to Product, UX, and Analytics counterparts on the Insights roadmap and broader data strategy.
- Represent the data organization to senior leadership and executive stakeholders, translating high-level initiatives into actionable team goals and reporting on key performance indicators.
- Partner with Application Engineers, Product Managers, and other engineering teams to translate business requirements into scalable pipeline and platform designs.
Hiring & Talent:
- Identify, recruit, and hire the best engineering and data science talent for the organization, including manager-level hires.
Now Requirements: "You’re a great fit for this role if:" then bullet list.
List:
- 8+ years of progressive experience across software engineering, data engineering, and/or data science, including experience leading multi-team initiatives.
- 5+ years of people management experience, including experience managing managers or senior individual contributors.
- At least 2+ years in healthcare, digital health, or health technology, using Agile delivery methodologies.
- Experience building complex software and data products within healthcare and/or government settings, with demonstrable success.
- Experience with data pipeline architectures (e.g., Apache Airflow), complex software systems, large-scale databases and/or cloud data warehousing platforms (e.g., Snowflake, Redshift, Databricks), including performance tuning and cost management.
- Working knowledge of applied data science/ML workflows and how they integrate with production data platforms.
- Strong knowledge of programming languages and paradigms, including SQL and Python.
- Experience operating in a regulated or compliance-sensitive data environment.
- Experience with Cloud infrastructure (AWS preferred) technologies.
- Excellent verbal and written communication skills; ability to represent technical strategy to non-technical executive audiences.
- BS/BA degree in Computer Science, Data Science, or a related field, or equivalent experience.
We could also include Qualifications/Skills but we can combine into Requirements. The instruction says use headings like Requirements, Qualifications, Skills. We have content for Requirements. Could also separate Skills but not needed.
Benefits: list from "Benefits provided by Unite Us:" then bullet points.
List:
- Medical, Dental, and Vision: We offer insurance to team members and eligible partners and dependents, including unlimited virtual mental health and acute medical visits.
- Wellness: Mental health benefits, such as the Employee Assistance Program (EAP) and wellness platform subscription, are available to all team members.
- Flexible Time Off: Take what you need, including volunteer days and mental health days. We also offer 14 paid, company-wide holidays.
- Paid Parental Leave: Adoptive parents are included.
- Employee Resource Groups: Join our ERGs to connect and engage with colleagues, like Military Veterans
- Spending Accounts: We offer tax-advantaged health savings accounts (HSAs), flexible spending accounts (FSAs), and commuter benefits.
- 401(k) + Employer Match: Enjoy matching, immediate vesting and financial wellness resources
- Additional Benefits: Life and AD&D - a company paid benefit, with the option to purchase additional coverage for yourself and your dependents
- Disability Coverage
- Accident Insurance
- Pet Insurance
- As part of this work at home job, we will provide you with all the necessary equipment to perform your duties, including a computer, mouse, keyboard as well as other items on our approved list of WFH supplies.
We need to keep each as list items.
Pay: "The target pay range for this role is: $225,000-$275,000. This salary range represents our target hiring range for this role. The proposed salary will be dependent on the candidate's skills, experience, and competencies, as well as location."
Schedule: remote, US based, preference for ET/CT time zones, may require 5-10% travel.
We'll put Schedule section with that.
Now produce HTML fragment.
We must not include or . Just the sections.
Let's craft:
About the Role
The Senior Director, Data Science & Engineering owns the technical strategy, architecture, and delivery of Unite Us' data platform and Insights product line, spanning both data engineering and data science disciplines. You will manage a team of managers and senior individual contributors, ensuring the group's roadmap balances technical soundness, business impact, and long-term platform scalability. You will partner closely with Product, Engineering, and Analytics leadership to translate company strategy into a coherent multi-team roadmap, while remaining close enough to the technical details to make sound architectural tradeoffs, evaluate build-vs-buy decisions, and unblock complex cross-team dependencies. You have deep knowledge of modern software & data platforms (cloud infrastructure, complex software systems, data pipelines, data warehousing, and applied data science/ML) and healthcare or social-care data standards, and you use that knowledge to raise the bar for engineering and analytical rigor across the group. You will build, mentor, and manage a group of engineering and data science managers, define what a high-performing team looks like, and hold the organization accountable to that bar. You are comfortable operating with significant autonomy, managing up and across the organization, and representing the data organization to executive stakeholders.
Responsibilities
- Team Leadership & People Development
- Lead, mentor, and grow a group of engineering and data science managers, and, through them, their teams of data engineers, analysts, and data scientists.
- Set and hold a high bar for technical talent across the data organization; define career ladders and growth paths for managers and senior ICs.
- Manage team-of-teams performance from both a technical and personnel perspective, including performance calibration and succession planning.
- Technical Strategy & Architecture
- Own the technical strategy and roadmap for the data platform and Insights product line, partnering with Product and Engineering leadership to balance innovation with business priorities.
- Establish and enforce engineering and analytical best practices across teams: code review standards, testing, CI/CD, model validation, monitoring, and incident response.
- Guide architecture decisions across data pipelines, the data lakehouse/warehouse, and applied data science/ML workflows, validating designs in AWS.
- Drive consistency and efficiency in data pipeline implementations and cross-product data/testing/deployment standards.
- Roadmap & Execution
- Own creation and execution of the group's multi-quarter roadmap, sequencing initiatives and aligning timelines with business goals.
- Manage capacity planning and prioritization across multiple teams, resolving contention and dynamically responding to shifting priorities.
- Identify and mitigate delivery risks before they become roadblocks, escalating judiciously and without damaging relationships.
- Cross-Functional Collaboration
- Act as a thought partner to Product, UX, and Analytics counterparts on the Insights roadmap and broader data strategy.
- Represent the data organization to senior leadership and executive stakeholders, translating high-level initiatives into actionable team goals and reporting on key performance indicators.
- Partner with Application Engineers, Product Managers, and other engineering teams to translate business requirements into scalable pipeline and platform designs.
- Hiring & Talent
- Identify, recruit, and hire the best engineering and data science talent for the organization, including manager-level hires.
- inside
- . That's okay but might be considered extra structure. The instruction: Use
- for any list of duties/requirements/benefits. It didn't forbid nested lists. However we could flatten: each responsibility area as a
- with the subheading as strong text and then the bullet points as separate
- ? But that would lose grouping. Probably nested is fine. Alternatively we could make each area a
- and then inside that
- we have a
- for the points. That's acceptable.
Now Requirements:
- 8+ years of progressive experience across software engineering, data engineering, and/or data science, including experience leading multi-team initiatives.
- 5+ years of people management experience, including experience managing managers or senior individual contributors.
- At least 2+ years in healthcare, digital health, or health technology, using Agile delivery methodologies.
- Experience building complex software and data products within healthcare and/or government settings, with demonstrable success.
- Experience with data pipeline architectures (
Requirements
- Team Leadership & People Development