• Analyze and understand data sources and design data models for capturing structured and unstructured data. • Perform statistical modeling, quantitative analysis, and data mining to extract valuable insights. • Develop and deliver Key Performance Indicators (KPIs) for various organizational needs in consultation with stakeholders. • Utilize data visualization tools to create reports and dashboards that communicate insights effectively. • Participate in Data Governance initiatives to establish data quality standards and measures. • Ensure the highest standards of data collection, recording, analysis, maintenance, storage, adaptation, retrieval, and transmission from various data sources. • Support the training and development of Data Stewards within various departments to enhance data analysis and visualization capabilities. • Stay updated with various Data Architectures to support diverse data needs of the organization. • Monitor and assess system performance for continuous improvements. • Collaborate with the Information Technology team to ensure the seamless integration of data tools and resources. • Provide technical assistance and direction to other Analysts for the purposes of resolving complex issues. • Provide direction in adoption of modern Data technologies as per the needs and demands of the organization.

Role Description We are looking for a Data Analyst for our Risk AI Platform - the group that owns the data and ML infrastructure behind Plata's credit decisioning. At the center of that infrastructure is our feature store: the system that turns raw external and internal data into the features that power our scoring models, both in research and in real-time production. The role sits at the intersection of data engineering, analytics, and ML: you'll spend most of your time in SQL, dbt, Python, and Snowflake, building reliable pipelines and making sure the features our models consume are correct, consistent, and well-monitored - offline and online. Challenges that await you: - Develop and maintain the feature store: design and optimize dbt models across our multi-layer pipeline, from raw ingestion through parsing, unification, and domain modeling to production-ready feature sets. - Onboard new external data sources (credit bureaus, alternative data, identity and scoring providers) into the platform — from raw parsing to production features. - Guarantee consistency between training and serving: build checks and monitoring that catch feature drift, mismatches, and data-quality issues before they reach a model. - Own data quality and observability for the features you ship — freshness, completeness, lineage, and reconciliation. - Work closely with data scientists and ML engineers to productionize features for scoring models, and help turn research feature logic into robust, tested pipeline code. - Improve our tooling, standards, and documentation so the whole team ships features faster and more safely. Qualifications - 2-3 years of experience in a data engineering, analytics engineering, or strongly engineering-oriented data analyst role. - Strong SQL: you're comfortable writing and optimizing complex queries. - Solid Python for data work (data pipelines, scripting, pandas). - Hands-on experience with dbt, or with building ETL/ELT pipelines you can map onto dbt. - A working understanding of ML — enough to reason about features, training/serving consistency, and how your pipelines feed a model. - A data-quality mindset: you care about correctness, reproducibility, and monitoring, not just getting the number out. - B1 or higher English level for effective communication with an international team. Requirements - Background in Risk, credit, lending, or fintech. - Experience with Snowflake (or a comparable cloud data warehouse) and a cloud platform (AWS). - Familiarity with feature stores, ML model registries. - Comfort with A/B testing and applied statistics. - Experience with orchestration and CI/CD for data. Benefits - Relocation support to one of our hubs — Cyprus, Serbia, Georgia or Kazakhstan — with assistance for the employee and their family. - Flexible work from one of our offices or remote. - Healthcare Coverage. - Education Budget: Language lessons, professional training and certifications. - Wellness Budget: Mental health and fitness activity reimbursements. - Vacation policy: 20 days of annual leave and paid sick leave.

Role Description The Senior Attorney will join our in-house legal team. Reporting directly to the General Counsel, you will serve as a trusted business partner across the organization—advising on corporate transactions, employment matters, and the privacy implications of our expanding digital and loyalty platforms. This role offers meaningful ownership, a collaborative culture, and the chance to shape legal strategy for a fast-growing company at a pivotal moment. This position requires broad legal expertise across multiple disciplines, including: - Corporate governance - Regulatory compliance - Employment law - Intellectual property - Data privacy - Litigation management - Commercial contracting - Real estate The Senior Attorney will exercise independent judgment while collaborating with global stakeholders to ensure legal compliance and support business objectives across multiple jurisdictions. Candidates for this role are required to be based within 50 miles of one of the following established Blue Bottle Coffee geographic locations: - The San Francisco Bay Area - Los Angeles Qualifications - Juris Doctor (J.D.) from an accredited law school, active bar admission, and good standing to practice law in California or New York. - 8-10 years of post-qualification experience (PQE), with a meaningful mix of law firm and in-house legal experience preferred. - Demonstrated expertise across at least two of the three core practice areas: corporate/commercial, labor and employment, and data privacy. - Strong transactional skills with hands-on experience drafting and negotiating complex commercial agreements. - Solid understanding of US employment law across multiple jurisdictions, including familiarity with California employment requirements. - Practical knowledge of US data privacy frameworks, particularly CCPA/CPRA, and experience advising on digital products and consumer data programs. - Excellent written and oral communication skills with the ability to explain legal concepts clearly to non-legal business partners. - Highly organized, self-directed, and comfortable managing multiple priorities in a fast-paced, growth-oriented environment. Requirements - Draft, review, and negotiate a broad range of commercial agreements including supplier contracts, real estate leases, licensing arrangements, and partnership agreements. - Support corporate governance activities including board meeting preparation, entity management across multiple jurisdictions, and subsidiary structuring. - Advise on regulatory compliance matters affecting multi-state retail operations, food and beverage regulations, and franchise law. - Work closely with Finance, Operations, and Business Development teams to provide timely, practical legal guidance on day-to-day transactions. - Manage a wide range of labor and employment matters including wage and hour compliance, workplace investigations, disciplinary actions, and terminations. - Advise HR on hiring practices, employee classification (exempt/non-exempt, employee/contractor), leave administration, and accommodation requests. - Handle employment-related disputes including demand letters, EEOC charges, state agency complaints, and civil litigation, coordinating with outside counsel as appropriate. - Draft and maintain employment policies, handbooks, and training materials that reflect current federal, state, and local law requirements. - Monitor legislative and regulatory developments in employment and labor law across key operating states and proactively advise the business on required adjustments. - Support union-related matters and collective bargaining processes where applicable. - Serve as a primary legal resource on data privacy and security matters, advising on compliance with CPRA, CCPA, and other applicable US and international privacy regulations. - Review and negotiate data processing agreements, SaaS contracts, and technology vendor agreements with a focus on data risk allocation and security obligations. - Partner with the Technology, Marketing, and Customer Loyalty teams to conduct privacy impact assessments and implement privacy-by-design principles. - Develop and maintain internal data privacy policies, records of processing activities, and incident response protocols. - Lead the company's response to data subject requests and coordinate breach notification procedures in compliance with applicable law. - Monitor emerging privacy legislation and regulatory guidance, advising leadership on compliance implications and required policy updates. - Manage outside counsel relationships and legal spend across practice areas. - Assist the General Counsel with special projects, board-level matters, and cross-functional legal initiatives. - Contribute to building and refining legal department processes, templates, and knowledge management systems. Benefits - Comprehensive health, dental, and vision coverage for eligible employees starting on your first day. - 401(k) plan. - Paid time off & paid volunteer hours. - 50% discount on all products, both online and in-cafe; this includes food, beverages, whole-bean coffee, and merchandise. - Flexible spending account & commuter benefits. - Employee Assistance Program. - Salary range: $168,000 - $253,000 a year.

• Provide technical and people leadership to design, build, and scale data and analytics solutions. • Own end-to-end delivery across multiple workstreams. • Establish repeatable engineering and governance standards. • Partner with Product, Engineering, Sales, and client stakeholders to grow and modernize analytics capabilities. • Lead, hire, coach, and retain a high-performing team; set goals, provide feedback, and drive career development. • Own the end-to-end lifecycle of data and analytics products—from discovery through build, release, adoption, and operations. • Operationalize cloud data products (Azure/AWS) using strong engineering practices: Git, CI/CD, automated testing, documentation. • Deliver scalable pipelines, automations, and accelerators for compliance/regulatory reporting and operations using Python, SQL.