United States onlyWhy Work Here?
At Arkatechture, we have a simple shared mission: to build a sustainable organization built upon three pillars: Do something meaningful, With a great team, Earning what you deserve.
Founded in 2012, Arkatechture has grown into a nationally recognized data and technology company, partnering with organizations across the fintech, AI, and financial services spaces. We combine deep industry knowledge with technical expertise to help our clients unlock the full potential of their data. Whether it’s modernizing infrastructure, building analytics platforms, or leveraging AI for smarter decision-making, we thrive at the intersection of innovation and impact.
Our team is made up of curious, collaborative, and community-minded professionals who are passionate about solving complex problems and staying ahead of what’s next in data and technology. While our roots are in New England, our reach is nationwide, and we support flexible, remote-friendly work to match.
We offer a competitive benefits package that includes:
- A flexible remote work policy with optional access to our Portland, Maine office
- A 4-day workweek after 3 years of service
- Generous paid time off, including 11 holidays
- Medical, disability, life insurance, and optional dental/vision
- 401(k) retirement plan with company match
- Training & certification reimbursement
- Milestone recognition programs, annual PTO increases, and more
All employees share our core values: put the team first, practice humility, take pride in everything we do, stay curious, care for our community & environment, take work seriously; ourselves not so much.
The Position
Arkatechture is seeking a Senior Data Analyst on the Product team to help drive the next generation of data and AI-powered solutions within our Arkalytics platform and client engagements.
In this role, you will operate at the intersection of analytics, AI and engineering, building intelligent data solutions that enhance decision-making and operational efficiency. You will work closely with cross-functional teams to design scalable data products, integrate AI capabilities, and push the boundaries of what our analytics platform can deliver.
The ideal candidate is a strong problem solver who can troubleshoot independently with hands-on experience applying AI tools (including GenAI) to real-world data problems.
How to Apply
Please send a cover letter and resume with your application. You must submit both documents to be considered for the position. We’re building a diverse team of people who care about doing meaningful work with great people. If that excites you, apply and let’s start the conversation.
Key Responsibilities
- Design, develop, and maintain advanced analytics solutions, including predictive models and Generative AI applications, using SQL, Python, and modern AI and BI tools
- Translate business problems into data-driven and AI-enabled solutions
- Responsible for end-to-end delivery of analytics and AI initiatives, from data exploration and feature engineering to model development, deployment, and ongoing optimization
- Design and engineer features from diverse data sources, including first-party and third-party data, to improve model accuracy and business relevance
- Operationalize models using robust MLOps practices, including deployment pipelines, automated scoring, version control, and scalable data integrations
- Define, monitor, and continuously improve model performance using appropriate metrics, including validation frameworks, drift detection, and retraining strategies
- Translate model outputs into scalable, user-friendly analytics products and dashboards (e.g., segmentation, propensity scores, next best product recommendations) for end-user consumption
- Design and evaluate experiments, including A B testing, to measure model effectiveness and quantify business impact
- Integrate AI, machine learning, and Generative AI capabilities into analytics workflows and product solutions
- Champion the adoption of Generative AI across teams by identifying and implementing use cases that improve productivity, insight generation, and client value
- Explore and implement solutions leveraging LLMs, prompt engineering, and AI-assisted analytics
- Educate and enable internal teams on AI and Generative AI best practices through documentation, training, and reusable frameworks
- Collaborate with Product, Engineering, and Services teams to evolve the Analytics Edge and AI roadmap
- Troubleshoot complex data, model, and system issues, identifying root causes and implementing scalable solutions
- Communicate insights, risks, and progress clearly to stakeholders, including both technical and non-technical audiences
- Create and maintain comprehensive technical documentation for data models, AI workflows, and processes
- Participate in Agile and Scrum ceremonies and contribute to continuous improvement of team processes
- Support client-facing discussions, demos, and training sessions as needed
Skills, Knowledge and Expertise
Requirements
- Bachelor’s degree in a relevant field or 5+ years of equivalent practical experience in data science, analytics, or applied AI
- Strong expertise in SQL and Python for data analysis, modeling, and production workflows
- Hands-on experience developing, deploying, and maintaining machine learning models in production environments
- Experience with MLOps platforms and practices, including tools such as AWS SageMaker or similar
- Experience working with modern data platforms such as Snowflake (preferred), Databricks, or BigQuery
- Hands-on experience with Generative AI technologies, including LLMs, prompt engineering, and frameworks such as LangChain, as well as vector databases and related tooling
- Proven experience applying AI and machine learning to real-world business or analytics problems with measurable impact
- Experience with BI and data visualization tools such as Tableau or Power BI
- Strong understanding of data warehousing, data modeling, and analytics architecture
- Familiarity with cloud platforms, preferably AWS
- Strong analytical thinking and problem-solving skills with attention to detail
- Excellent communication skills, with the ability to convey complex concepts to both technical and non-technical audiences
- Experience working in Agile or Scrum environments
Preferred Experience
- Experience building or supporting AI-powered analytics products or features
- Experience with Claude Code or Cortex code
- Experience working with financial institutions (credit unions, banks)
- Experience on a Product or innovation-focused team
- Demonstrated curiosity and passion for emerging AI technologies
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