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

On-Site | Full-time

Compensation: $250K - $350K

We are hiring on behalf of our client, an industry-leading accelerator program focusing on the intersection of blockchain, cryptocurrency, and artificial intelligence is seeking a highly autonomous and proactive Data Scientist to join its core engineering group. Having backed over 300 high-growth startups now collectively valued in the tens of billions, our client provides an exceptional launchpad for high-impact innovation.

In this role, the candidate will report directly to the Chief Technology Officer and take full end-to-end ownership of data products—from defining initial requirements to deploying reliable production systems. This is an entirely onsite role based in New York City (NYC) designed for an ambitious, self-directed builder who thrives in a fast-paced, high-agency environment without requiring extensive product management or dedicated platform engineering support.

Key Responsibilities

Location: Remote - Europe preferred, must be able to work European hours

Remote | Full-time

Compensation: $120K - $150K

Our client is a dynamic, forward-thinking, fully remote organization with an ambitious roadmap and a strong commitment to engineering excellence.

Seeking a Senior Fullstack Engineer to work at the intersection of frontend and backend development. In this role, the engineer will build and maintain both a React-based trading user interface and the TypeScript backend services that power high-performance trading platforms. The position involves full feature ownership—from crafting responsive, real-time interfaces to designing the APIs, data pipelines, and indexing solutions that feed them.

The ideal candidate possesses a strong passion for trading, engineering rigor, security, and velocity, backed by over six years of professional experience and a dedication to code quality and state-of-the-art software testing practices.

Key Responsibilities

Frontend Development & Performance

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

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.

Location: London, England, GB

On-Site | Full-time

Compensation: £110K - £150K GBP

Our client is a high-velocity, London-based applied research lab reshaping the future of B2B operations and sales. By building highly intelligent, agentic workflows and automating high-volume execution, they empower businesses to focus on deep, high-value human connections. Operating as a talent-dense, seed-stage, revenue-generating startup, the team ships to production daily, tackles highly ambiguous engineering challenges, and works at the cutting edge of AI capabilities.

They are seeking a Staff Engineer to serve as one of the most senior Individual Contributors (ICs) on the engineering team. In this player-coach role (~70% IC, ~30% technical leverage, mentoring, and architectural leadership), the successful candidate will not simply execute tickets, but will instead own complex, ambiguous problem spaces end-to-end.

This is a fully on-site role based in Piccadilly, London, designed for a builder who thrives in a fast-paced, highly collaborative, and high-standard engineering culture.

Key Responsibilities

Location: London, UK

On-Site | Full-time

Compensation: Competitive Compensation

Our client is an early-stage, high-impact, revenue-generating AI startup that is fundamentally redefining business automation. While most applied AI companies focus on selling software tools, this organization sells completed business outcomes—delivering highly automated, autonomous pipelines that directly close revenue for clients ranging from fast-growing startups to Fortune 500 enterprises.

With strong product-market fit, consistent month-over-month growth, and a clear roadmap, the engineering team is currently scaling up. This is a rare opportunity to join an elite, tight-knit, and highly leveraged engineering team where every line of code directly drives revenue and shapes foundational systems from scratch.

The team operates in a fast-paced, high-momentum environment that values intense collaboration. To maintain this high-engagement culture, this role is 100% on-site (five days a week) at the client's office in Piccadilly, London.

Key Responsibilities

About DSI

Founded in 1984, DSI is a family-owned company committed to delivering exceptional value and measurable results to our clients and partners. Our comprehensive services include sales management, marketing support, hardware logistics, immersive training, engineering expertise, and proprietary software solutions—all designed to drive growth and operational efficiency.

At DSI, we believe strong relationships are the foundation of lasting success. We serve as a one-stop solution across a range of markets—including mobility, broadband, video, commercial, residential, Lodging & Institutions, and Multi-Dwelling Units—empowering our sales partners to uncover new opportunities and maximize their potential.

Role Summary

We are seeking a Business Intelligence (BI) Developer to join our Data and Analytics department. This role is critical for transforming raw data into actionable business insights through complex analysis, mining, and visualization. You will work closely with team leaders to understand the nuances of DSI’s business, ensuring we capture, report, and act on data related to customer and operational performance.

Key Responsibilities

Location: New York, United States (Hybrid) 

Hybrid | Full-time

Compensation: $180K - $320K

Our client is a high-volume decentralized finance (DeFi) protocol based on Arbitrum, facilitating leveraged trading of real-world assets—including commodities, forex, indices, and equities—alongside crypto with full self-custody.

The client is seeking a Senior Data Engineer to spearhead infrastructure initiatives, optimize high-throughput data processing, and establish modern data engineering best practices. This role will focus on scaling data pipelines and building an advanced infrastructure layer that empowers engineering teams with self-service capabilities for deploying applications, requesting infrastructure, and managing monitoring systems.

Key Responsibilities

Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.

We are seeking an experienced Lead Consultant / Project Manager to drive the delivery of strategic data and AI-powered solutions for a leading financial services client. This role combines consulting, business analysis, product strategy, and project leadership, requiring close collaboration with business stakeholders, technical teams, and executive sponsors.

The ideal candidate will have a strong background in Wealth Management, Insurance, or Financial Services and possess the ability to translate complex business workflows into scalable digital products and analytics solutions.

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.