Worth AI

👥 11-50💰 $12,000,000 Seed over 1 year agoArtificial Intelligence (AI)Business Intelligence Risk Management FinTech

Worth AI is a technology-driven company offering innovative solutions, leveraging Euro as its primary currency and utilizing Cloudflare Hosting for robust online services. With a dedicated team of 11-50 employees, it is currently looking to expand its workforce by hiring Back End and Full Stack Software Engineers.

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🔥 Data Infrastructure Engineer

Posted 1 day ago

📍 United States

🔍 Software Development

🔧 Requirements

Strong programming skills in Python, Node.js.
Proficient in SQL and experience with distributed query engines (e.g., Trino, Presto).
Experience with cloud-native data platforms such as AWS Glue
Hands-on experience with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation).
Familiarity with containerization and orchestration tools such as Kafka and Kubernetes.
Solid understanding of data governance, quality frameworks, and data lifecycle management.
Experience in streaming data architecture and tools like Apache Kafka, Kinesis, or Pub/Sub.
Background in supporting machine learning or analytics platforms.
Exposure to data mesh, data contracts, or modern data stack concepts.
Knowledge of DevOps principles applied to data systems.

💡 Responsibilities

Design, build, and maintain scalable and resilient data infrastructure in a cloud environment (AWS, Azure, or GCP).
Develop and maintain ETL/ELT pipelines using orchestration tools such as Airflow, Dagster, or dbt.
Optimize data workflows for reliability, performance, and cost efficiency across structured and unstructured datasets.
Manage data lake and data warehouse environments (e.g., Snowflake, BigQuery, Redshift, Delta Lake).
Ensure data security, privacy, and compliance, including role-based access control, data encryption, and audit logging.
Collaborate with data scientists, analysts, and product teams to ensure data accessibility, accuracy, and availability.
Support real-time and batch data processing frameworks, including Kafka, Spark, Flink, or similar tools.
Monitor, troubleshoot, and improve the observability and performance of data systems using tools like Prometheus, Grafana, or Datadog.
Maintain CI/CD pipelines for data infrastructure using Terraform, GitHub Actions, or similar tools.

Posted 1 day ago

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🔥 Product Manager - DATA

Posted 1 day ago

📍 United States

🔍 Computer Software

🔧 Requirements

Proven experience as a Product Manager + ML with 3+ years in data-centric or analytics-focused products
Strong understanding of data platforms, ETL/ELT pipelines, and data warehousing concepts
Familiarity with data tools such as Snowflake, BigQuery, dbt, Airflow, or similar technologies
Experience working cross-functionally with data engineers, analysts, and scientists
Track record of successfully shipping data products or platforms to internal or external users
Comfort with SQL, data exploration, and metrics analysis to inform product decisions
Experience aligning with senior leadership and translating business needs into data product strategies
Excellent written and verbal communication skills; able to distill complex topics for varied audiences
Creative and strategic thinking with the ability to solve ambiguous problems
Highly coachable, collaborative, and excited to challenge the status quo

💡 Responsibilities

Engage with internal and external users to uncover data-related needs, pain points, and opportunities
Identify and prioritize data product opportunities, including data pipelines, APIs, dashboards, and reporting tools
Partner with ML engineers to operationalize models and ensure seamless integration into customer-facing products
Define metrics to measure model performance and business impact
Translate user and business requirements into clear, actionable product use cases and specifications
Partner with data engineering and data science teams to deliver models, infrastructure, and analytical tools
Work with design to develop mockups, user flows, and interactive prototypes for data-related features
Own the product backlog and ensure user stories are technically groomed and ready for development
Define, track, and refine key metrics and KPIs that measure product success and data platform performance
Work closely with QA to ensure robust data validation, integrity, and UAT across releases
Ensure data products are well documented, including schema definitions, data dictionaries, and release notes
Drive prioritization discussions based on customer value, data impact, and strategic fit
Provide real-time decision-making support to developers during sprints and releases
Advocate for data quality, governance, and scalability as core elements of product development
Collaborate with operations and support teams to triage and resolve data issues
Contribute to the evolution of product management processes, especially around data-centric development

Posted 1 day ago

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🔥 VP of Data, Analytics and AI

Posted 2 days ago

📍 United States

🔍 Computer Software

🔧 Requirements

10+ years in data leadership roles, including at least 5 years leading large-scale data initiatives in fast-paced, data-driven environments.
Experience with risk technology or credit modeling in enterprise contexts is a strong plus.
Proven expertise in monetizing data assets and building governance structures at scale.
Strong understanding of data platforms (e.g., Snowflake, Databricks), cloud architecture, data pipelines, and modern analytics tooling.
Demonstrated ability to lead multidisciplinary teams, craft vision and strategy, and drive tactical execution.
Outstanding communication and stakeholder management skills, with the ability to convey complex data concepts to technical and non-technical audiences.
Deep experience in data science, machine learning, AI, and credit or risk modeling.
Strong problem-solving and data interpretation skills with a focus on delivering results.

💡 Responsibilities

Lead a growing team of approximately five data professionals across engineering, analytics, data science, and governance.
Be a hands-on leader who actively engages in code reviews, model reviews, and technical deep dives to stay connected to the day-to-day realities of engineering and data science work.
Set a high technical bar while mentoring and developing team members, fostering a culture of innovation, ownership, and collaboration.
Lead the end-to-end strategy for acquiring first-party, second-party, and third-party data sources aligned to business priorities.
Evaluate and negotiate data licensing agreements and strategic partnerships to grow our data asset portfolio.
Design robust, scalable, and compliant ingestion pipelines for efficient data integration and enrichment.
Utilize data science, machine learning, and AI techniques to design, test, and deploy advanced risk, fraud, and credit scoring models.
Identify, define, and execute on opportunities to monetize data assets—both directly and through data-enabled products and services.
Partner closely with Product, Sales, Marketing, Strategy, and Customer Success to integrate data insights into go-to-market initiatives and client-facing solutions.
Translate data into actionable business intelligence that informs strategy and drives measurable business growth.
Build scalable, repeatable processes for data management—spanning integration, transformation, quality assurance, and delivery.
Champion the adoption of modern data platforms and tools (e.g., Snowflake, Databricks, dbt) to support real-time decision-making and automation.
Develop and lead a high-performing data team across engineering, analytics, data science, and governance, fostering a culture of innovation, collaboration, and accountability.
Own and evolve data governance frameworks to ensure integrity, quality, security, and compliance with global regulations (e.g., GDPR, CCPA).
Establish clear data ownership and stewardship models, along with standardized policies for access, lineage, and privacy.
Proactively manage data risk and embed ethical practices into all aspects of data use and monetization.
Partner with engineering, product, finance, and other internal teams to ensure alignment on data initiatives.
Serve as the internal advocate for data as a strategic asset, ensuring organizational alignment around data value and strategy.

Posted 2 days ago

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🔥 Director of Data Science

Posted 2 days ago

📍 United States

🧭 Full-Time

🔧 Requirements

Bachelor’s degree and 8+ years of professional experience, or Master’s degree and 6+ years, or PhD and 4+ years, in a quantitative field such as Computer Science, Statistics, Applied Mathematics, or Engineering.
Proven leadership experience managing data science or machine learning teams in fast-paced, agile environments.
Deep expertise in statistical modeling and machine learning techniques (e.g., regression, time series, clustering, ensemble methods, simulation, NLP, deep learning, etc.).
Hands-on proficiency in Python and SQL; familiarity with R or other languages is a plus.
Practical experience with ML libraries and frameworks such as Scikit-learn, TensorFlow, Keras, PyTorch, Statsmodels, NumPy, and SciPy.
Strong understanding of data architecture and MLOps practices in cloud environments such as AWS, Azure, or GCP.
Excellent data storytelling and executive communication skills; confident in building and delivering compelling visual presentations (e.g., Tableau, PowerBI).
Deep understanding of Agile methodologies such as Scrum or Kanban.

💡 Responsibilities

Lead, mentor, and scale a high-performing team of data scientists while fostering a culture of innovation, collaboration, and continuous learning.
Oversee the end-to-end development of machine learning models—design, training, validation, and deployment—within cloud-based production environments.
Partner with product, engineering, and business teams to identify opportunities for data science solutions, define success metrics, and deliver measurable impact.
Drive the integration of large-scale data systems and pipelines to power intelligent, adaptive models that reflect changing customer, market, and business dynamics.
Ensure rigorous model monitoring, governance, and retraining protocols to maintain accuracy, fairness, and compliance.
Communicate technical results and strategic insights clearly and persuasively to senior leadership and non-technical stakeholders.
Champion the adoption of advanced analytics tools, frameworks, and best practices across the company.

AWSLeadershipPythonSQLAgileCloud ComputingData AnalysisGCPKerasMachine LearningNumpyPyTorchTableauAlgorithmsData scienceData StructuresPandasTensorflowCommunication SkillsData visualizationTeam managementData modeling

Posted 2 days ago

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🔥 Senior Data Engineer

Posted 2 days ago

📍 United States

🔍 Computer software

🔧 Requirements

7+ years of proven experience as a Senior Data Engineer or similar role, preferably in a software or technology-driven company with experience processing several to several hundreds of Gigabytes of data or more
In-depth knowledge of data modeling, data warehousing, and database design principles.
Strong programming skills in Python, SQL, and other relevant languages.
Experience with relational and NoSQL databases, such as PostgreSQL, MySQL, MongoDB
Proficiency in data integration and ETL tools, such as Apache Kafka, Apache Airflow, or Informatica.
Familiarity with big data processing frameworks, such as Hadoop, Spark, or Flink.
Knowledge of cloud platforms, such as AWS, Azure, or GCP, and experience with data storage and processing services in the cloud.
Understanding of data governance, data privacy, and data security best practices.
Strong problem-solving and troubleshooting skills, with a focus on data quality and system performance.
Excellent communication and collaboration skills to work effectively with cross-functional teams.
Prior collaborative work with data scientists or machine learning professionals with respect to sourcing, processing and scaling both input and output data
Comfortable going through documentation of third-party API’s and identifying best procedures for integrating data from API’s into broader ETL processes

💡 Responsibilities

Design, build, code and maintain large-scale data processing systems and architectures that support AI initiatives.
Develop and implement data pipelines and ETL processes to ingest, transform, and load data from various sources.
Design and optimize databases and data storage solutions for high performance and scalability.
Collaborate with cross-functional teams to understand data requirements and ensure data quality and integrity.
Implement data governance and data security measures to protect sensitive data.
Monitor and troubleshoot data infrastructure and pipeline issues in a timely manner.
Stay up-to-date with the latest trends and technologies in data engineering and recommend improvements to enhance the company's data capabilities.

Posted 2 days ago

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🔥 Full Stack/ Back End (Javascript/Node.js) Engineer - Focused on Data Integration

Posted 11 days ago

📍 United States

🔍 Software Development

🔧 Requirements

7+ years of proven experience as a Full Stack/ with heavy back end experience designing and developing web applications.
Experienced Engineer who has prior experience focusing on DATA - whether it be Data Infrastructure, Data Platform or Data Engineering
Proven experience working with ETL/ELT Data Flows and data processing
Proficiency in programming languages such as JavaScript, Python, Node.js
Strong knowledge of front-end technologies including JavaScript frameworks (e.g., React/Typescript).
Experience with back-end technologies of Node.js, Express.js, and relational databases (e.g., MySQL, PostgreSQL).
Familiarity with cloud technologies (e.g., AWS) and containerization (e.g., Docker, Kubernetes, Argo CD, Kafka)
Knowledge of version control systems (e.g., Git) and software development methodologies (e.g., Agile, Scrum).

💡 Responsibilities

Design, develop, and maintain scalable and high-performing web applications using modern technologies and frameworks.
Determine data requirements and develop solutions that support strategic goals.
Collaborate with cross-functional teams to gather and analyze user requirements and translate them into technical specifications.
Write clean, secure, and efficient code to ensure high-quality software development.
Conduct thorough testing and debugging to ensure software functionality and reliability.
Participate in code reviews and provide constructive feedback to improve code quality and maintainability.
Keep up to date with industry trends and emerging technologies to continuously enhance the software development process.
Completes all technical tasks assigned in each sprint
Understands and improves all code bases currently under development
Keep products up to date with new technology
Assist in product releases, revisions, patches and code reviews
Support and troubleshooting issues with existing code
Collaborate closely with other teams within the organization
Researches new technology and best solutions for each problem
Be transparent in sprint planning/retrospectives

AWSBackend DevelopmentDockerNode.jsPostgreSQLSoftware DevelopmentAgileCloud ComputingETLExpress.jsFull Stack DevelopmentGitJavascriptKafkaKubernetesMySQLReact.jsTypeScriptData engineeringCI/CDRESTful APIsDevOpsData modeling

Posted 11 days ago

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🔥 Partnerships - (Channel) Sales Account Executive

Posted about 2 months ago

📍 United States

🧭 Full-Time

🔍 Computer Software

🔧 Requirements

Proven experience in Enterprise Partnership Sales Management and Business Development roles within FinTech
Proven track record of developing, managing, and closing a qualified pipeline within a portfolio of partners in a quota-carrying role, consistently achieving or exceeding targets.
Experience working in small or mid-size startups
Established relationships with private equity firms for partnership development
Proven success in managing partner programs within the banking partner ecosystem
Strong understanding of AI and its applications in the business world
Excellent communication, negotiation, and interpersonal skills
Ability to identify and evaluate partnership opportunities that align with strategic goals
Experience in contract negotiation and agreement execution
Ability to collaborate effectively with cross-functional teams and external stakeholders
Analytical skills to monitor and evaluate partnership performance
Experience in the computer software industry is highly preferred
Ability to thrive in a fast-paced and dynamic environment
Strategic thinking and problem-solving abilities
Experienced in FinTech, AI or Data
Experience with KYC, KYB, fraud identification or other data providers

💡 Responsibilities

Identify and evaluate potential FinTech partnership opportunities that align with Worth AI's strategic goals and focus on Private Equity-backed firms.
Build and nurture a portfolio of strategic partnerships
Develop a comprehensive partnership strategy and framework to guide selection, engagement, and relationship management.
Establish and maintain relationships with key stakeholders and decision-makers of potential partners
Negotiate and execute partnership agreements, ensuring alignment of objectives and mutual value creation
Collaborate with cross-functional teams to integrate partner solutions with our AI platform
Monitor and analyze partnership performance, providing regular reports and recommendations for improvement
Stay informed about industry trends, competitive landscape, and emerging technologies to identify new partnership opportunities

Posted about 2 months ago

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🔥 Enterprise Account Executive (Sales)

Posted 4 months ago

📍 United States

🔍 Computer software industry

🔧 Requirements

Proven track record of at least 3 years in B2B sales, preferably in the computer software industry.
Experience working in data/credit/risk industry.
Strong understanding of AI and its applications in the business world.
Excellent communication, negotiation, and presentation skills.
Ability to build and maintain strong relationships with clients.
Self-motivated and results-oriented with a proven ability to meet and exceed sales targets.
Strong business acumen and ability to understand complex client needs.
Coachable and able to take direction and feedback well, yet being forward-thinking to challenge the status quo.
Consultative, collaborative approach to selling and relationship-building.
Willingness to travel as required.
Prior experience in Risk, Underwriting, credit and/or Payments Industry.

💡 Responsibilities

Drive new business growth by identifying and prospecting potential clients in the computer software industry.
Build and maintain strong, long-lasting relationships with key decision-makers and stakeholders.
Conduct in-depth client needs analysis to understand their business challenges and objectives.
Present and demonstrate Worth AI's products and services to potential clients effectively.
Collaborate with the internal team to develop customized proposals and solutions.
Negotiate contracts and close new business deals while managing sales cycles effectively.
Act as a trusted advisor to clients, providing ongoing support and ensuring satisfaction.
Devise and implement business plans to target and reach prospective customers.
Be a brand ambassador in the local and industry communities through event presence and thought leadership.
Desire to actively support, drive, and improve the culture of the company.

Artificial IntelligenceNegotiationRelationship managementSales experienceCRM

Posted 4 months ago

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