Data Lead

Allara is a comprehensive women’s health provider that specializes in expert, longitudinal care that supports women through every life stage. Trusted by over 40,000 women nationwide, Allara makes expert healthcare accessible by connecting patients with multidisciplinary care teams that have a deep understanding of hormonal, metabolic, and reproductive care. Allara provides ongoing support for hormonal conditions like PCOS, chronic conditions like insulin resistance, and life stages like perimenopause, helping patients see improved health outcomes. As one of the fastest-growing women’s health platforms in the U.S., Allara is bridging long-overlooked gaps in healthcare for women.

The Opportunity 

This is a hands-on leadership role, driving data strategy for our rapidly growing organization across Data Science, Analytics, and Data Engineering. We need someone who can accelerate our data capabilities and build the foundation that takes us to the next stage of growth.

This isn't a typical analytics role. You'll be building the data infrastructure that our clinical, product, and business teams rely on to make decisions that affect real patient outcomes. You'll own our analytics systems, establish data practices that scale, and prepare us for a future where structured care plan data and outcomes measurement are core to our competitive advantage. If you've been waiting for the opportunity to shape a data organization rather than inherit one, this is it, as you’ll have a tremendous opportunity to grow with Allara and leverage our unique and vast dataset. 

Location: Hybrid (NYC). We value in-person collaboration and aim for at least three days per week in our NYC office, with flexibility as needed.

Your Impact 

• Build the data infrastructure we'll rely on for the next 5 years. Design and implement our data warehouse, establish ETL/ELT pipelines, and create the architecture that turns messy healthcare data into reliable insights. You'll make critical decisions about our stack and set standards that last.
• Create unified visibility across the patient journey. Stitch together data from clinical systems, product analytics, and marketing/growth tools to build end-to-end views of how patients flow through our experience. Connect the dots between acquisition source, product engagement, clinical outcomes, and retention so we can answer questions like: Which channels bring the highest-value patients? How does app usage correlate with health improvement? Where do we lose people, and why?
• Own analytics that drive clinical and business outcomes. Partner directly with clinical ops, product, and leadership to answer questions like: Which interventions improve patient outcomes? Where are bottlenecks in our care delivery? What cohorts should we prioritize? Your analysis will directly inform resource allocation, product roadmap, and clinical protocols.
• Prepare us for outcomes-based care. Structure and instrument data collection for care plans, clinical workflows, and patient outcomes. Build the data models that let us prove our clinical efficacy and eventually support value-based care contracts.
• Enable rigorous experimentation and product optimization. Partner with product and growth marketing functions to design and analyze A/B tests that drive confident decision-making. Set up experimentation infrastructure using tools like Amplitude or similar platforms. Ensure we're measuring what matters with proper statistical rigor—from sample size calculations to significance testing to understanding when results are actionable vs. noise.
• Establish the discipline. Set standards for data quality, documentation, and governance. Make data accessible to non-technical stakeholders while maintaining rigor. Create a culture where decisions are grounded in evidence, not instinct.
• Scale yourself. Document your work, build tools that empower others, and hire your eventual team. You're not just doing the work—you're establishing how data work gets done here.

Required Qualifications 

• You've built data systems from scratch. You have 5+ years combining analytics and engineering—you can write complex SQL, build pipelines in Python or similar, and have strong opinions about data modeling. You've worked with modern data stacks (dbt, Airflow, Fivetran, Snowflake, BigQuery, or equivalents) and can evaluate trade-offs between tools.
• You're fluent in statistics and experimentation. You know how to design and analyze A/B tests properly—power calculations, multiple testing corrections, confidence intervals, statistical significance vs. practical significance. You can both set up the technical infrastructure for experimentation and partner with product teams to interpret results correctly.
• You've connected the full funnel. You have hands-on experience building analytics that span acquisition, product engagement, and downstream outcomes. You've wrestled with identity resolution, attribution models, and connecting behavioral data to business metrics. You know how to create coherent narratives from fragmented data sources.
• You translate ambiguity into action. You're comfortable when the question is "what should we know?" rather than "pull this metric." You probe stakeholder requests, identify the real question underneath, and deliver insights that change decisions.
• You care about healthcare. Experience in healthcare or similarly regulated industries is strongly preferred. You understand why HIPAA matters, what clinical outcomes mean, and why data quality isn't negotiable when patients are involved.
• You communicate insights, not just numbers. You can explain technical concepts to non-technical audiences. Your dashboards tell stories. Your documentation means the next person can pick up where you left off.
• You have an ownership mentality. You're energized by autonomy and responsibility. You ship incrementally rather than waiting for perfection. When something breaks, you fix it. When something's missing, you build it.
• You're pragmatic about scope. You know when to build custom vs. buy off-the-shelf. You optimize for impact, not elegance. You're comfortable with 80/20 solutions that unlock the next question.

Preferred Qualifications

• Experience implementing experimentation platforms (Amplitude Experiment, Optimizely, LaunchDarkly, or similar)
• Background with clinical data standards (HL7, FHIR) or outcomes research
• Experience in consumer health, digital health, or health tech environments
• Early-stage startup experience where you wore multiple hats
• Experience working with LLMs, and with key concepts such as fine-tuning, RAG, MCP, etc.

What Allara Offers  

Compensation & Career Growth

• $120,000 - $160,000 with opportunities for advancement
• Equity 
• Professional development & employee learning programs

Actual compensation will be determined based on a variety of factors, including but not limited to: candidate experience, education, certifications, and skill set. In addition to base salary, our total compensation package includes equity, comprehensive health benefits (medical, dental, vision), generous paid time off, and additional wellness and professional development perks.

Work Environment & Flexibility

• 3-day hybrid in NYC
• Unlimited PTO & 11 company holidays
• Annual onsite in NYC

Health & Wellness

• Medical, dental, and vision benefits
• Health Savings Account (HSA) & Flexible Spending Account (FSA)
• Long- and short-term disability coverage
• Annual employee wellness stipend

Family & Future Planning

• 401(k) plan
• Parental leave & family planning support benefits

Additional Perks

• Company-issued laptop
• Annual work-from-home stipend
• A collaborative, mission-driven culture focused on improving patient care

At Allara, we believe in celebrating everything that makes us human and are proud to be an equal-opportunity workplace. We embrace diversity and are committed to building a team that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better we can serve our members. We’re an Equal Opportunity Employer and do not discriminate against candidates or patients based on race, color, gender, sexual orientation, gender identity or expression, age, religion, disability, national origin, protected veteran status, or any other status protected by applicable federal, state, or local law.