About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $150M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services - operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company - product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together - the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them - which is exactly the job we're hiring for.

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for a Senior Manager / Associate Director to lead delivery workstreams within a large-scale enterprise Data Governance, Architecture & Controls Program.

Responsibilities:

Azumo is looking for a highly technical and hands-on DevSecOps Engineer / Security Solutions Lead to own and strengthen the security posture of our platform, infrastructure, and AI-driven systems.

This is a proactive, operationally-focused role—not just policy work. You will actively secure systems, remediate vulnerabilities, and collaborate across engineering and compliance to ensure continuous resilience. Working in a remote-first, high-trust engineering culture, you will join us as we scale rapidly following our Series A funding to power the future of modern financial infrastructure.

Location: Remote Latin America

In this role, you will secure and improve the systems that power our FinTech ecosystem while also serving as a key representative of our security program during customer and partner due diligence processes.

Key Responsibilities

Security Engineering & System Hardening

● Secure and harden cloud infrastructure, applications, APIs, internal systems, and operational workflows. · Implement and maintain security controls across production environments, CI/CD pipelines, cloud infrastructure, and internal tooling.

● Work directly with engineering teams to remediate vulnerabilities and improve secure development practices.

Location: New York, United States (Office) - Must be able to work office based in NYC

On-Site | Full-time

Compensation: $300K - $375K

Our client, a premier venture accelerator backing high-growth technology and emerging-tech startups, is seeking an experienced and self-directed Senior Machine Learning Engineer to join their in-house engineering team in New York City.

Reporting directly to the Chief Technology Officer (CTO), the Senior Machine Learning Engineer will take full ownership of features throughout the product lifecycle—from requirements definition to production deployment. This onsite role requires an entrepreneurial mindset and deep technical execution to turn loosely defined problems into robust, production-ready machine learning and LLM-based systems without reliance on large engineering teams or dedicated project managers.

Key Responsibilities

We are looking for a Senior Data Analyst to lead product analytics across the GoMining ecosystem.

You will own the development of our product analytics capabilities — from event tracking and funnel analytics to A/B testing infrastructure, AI-powered insights, and product performance reporting.

This role is ideal for someone who combines deep analytical expertise with hands-on experience building scalable analytics systems and leveraging AI to improve decision-making.

We are looking for a Senior Data Analyst to lead Retention & Marketing Analytics across the GoMining ecosystem.

You will partner closely with our Marketing and CRM teams to build a data-driven retention strategy — from customer segmentation and lifecycle analytics to A/B testing, personalization, and automated performance insights.

This role is ideal for someone who combines strong analytical expertise with a deep understanding of user behavior, CRM, and retention mechanics.

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for an Analyst / Senior Analyst to support a large-scale enterprise data governance program with one of our leading clients.

Responsibilities:

• Document data lineage from Tier 1 consumption points through analytical data stores to systems of origin, capturing findings in the client's preferred tooling.
• Support the design, development, and deployment of ADS components, data pipelines, and data quality controls (DQ rules, variance analysis, anomaly detection, comprehensiveness checks) on GCP.
• Contribute to data modeling and target-state landscape design, support SME interviews, and work closely with engineering teams and business data office stakeholders day-to-day.
• Operate as the bridge between engineering, enterprise architecture, and data office stakeholders, and present findings and recommendations directly to senior client leadership.
• Bridge business and technical requirements by translating insights from the business data office into actionable engineering tasks.

Requirements

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for a Senior Manager / Associate Director to lead delivery workstreams within a large-scale enterprise Data Governance, Architecture & Controls Program.

Responsibilities:

About LawnStarter

LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with over $100M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services - operating across three brands (LawnStarter, Lawn Love, Home Gnome) on a single shared platform.

About Analytics at LawnStarter

We're a small, senior analytics team supporting the entire company - product, marketing, operations, and finance all run on the data we serve. The foundation is solid: a centralized Redshift data warehouse where all source data lands, modeled in dbt and orchestrated by Airflow, with Segment feeding event data in. You won't be stitching scattered sources together - the platform exists; your job is to make it trustworthy and keep it that way. We're mid-migration to Lightdash as our single BI platform, replacing Tableau and Metabase.

Here's the honest gap: everyone on the team today is an analyst. Data quality, tracking standards, and platform hygiene get done as side work, squeezed between analyses. Nobody wakes up thinking about them - which is exactly the job we're hiring for.

About the Role

We are seeking an experienced Senior Databricks Data Quality Engineer to lead the design, implementation, and automation of enterprise-scale data quality frameworks within a Databricks environment. The successful candidate will play a key role in establishing data quality controls, profiling frameworks, remediation processes, and AI-assisted quality monitoring across a large-scale data platform consisting of 170+ datasets and over 1,300 Critical Data Elements (CDEs).

This role requires strong expertise in Databricks, PySpark, Delta Lake, MLflow, and modern data quality management practices.