{"id":2991886,"url":"https://alion.io/job/neurons-lab-forward-deployed-architect-credit-analytics-ml-platforms","title":"Forward-Deployed Architect, Credit Analytics & ML Platforms","company":{"id":4957,"name":"Neurons Lab","domain":"neurons-lab.com","url":"https://alion.io/company/neurons-lab","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"staff","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["BG","CY","CZ","HU","IT","PL","RO","RS","ES","UA","AL","EE","GR","LT","MT","MD","MK","PT","SK","SI"],"hiring_countries_total":20,"salary":null,"salary_estimate":{"min_usd":68000,"max_usd":115000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":28},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Streamlit","optional":false}],"status":"live","first_seen_at":"2026-10-21T09:58:48Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-25T18:29:03Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"About the role\nWe are looking for a hands-on Forward Deployed Engineering (FDE) Architect to help develop a credit analytics platform for a regulated financial-services business operating in the UK and Ireland.\nThe platform brings together lending and servicing data to support portfolio analysis, credit-risk modelling and better business decisions. Current work covers probability of default, redemption and prepayment, expected credit loss, and interactive analytics. The next challenge is to turn this work into a reliable, maintainable platform that can support different portfolios and client needs.\nYou will work directly with the client’s business and technology teams, alongside a credit-domain and modelling lead and other engineers. You will own the engineering architecture, contribute production code, and help the team decide what to build and how to deliver it. We need someone who can question assumptions, propose simpler alternatives and explain technical trade-offs clearly.\nWhat you will do\nTranslate business problems into an architecture, practical delivery plan and clear acceptance criteria. Identify gaps in requirements, data and dependencies before they become delivery problems.\n\nDesign the path from working models and dashboards to a production-ready ML platform. Make deliberate choices about shared components, portfolio-specific configuration, model calibration and future client onboarding.\n\nBuild and improve reproducible workflows for data preparation, feature engineering, training, validation, scoring and deployment. Establish clear versioning for code, data, models and calibration logic.\n\nWork with the modelling lead on how probability of default, prepayment, lifetime risk and loss estimates are calculated, tested and exposed to applications. Keep business definitions consistent across models, tables and dashboards.\n\nStrengthen the data foundation: trace results to source, investigate data-quality issues, document assumptions and build automated checks around important transformations.\n\nImprove the reliability of the Snowflake-backed analytics application, including deployment, testing, permissions and integration with model outputs.\n\nPut appropriate MLOps practices in place, including repeatable releases, monitoring, failure handling, rollback and operational documentation.\n\nDesign for privacy, access control, auditability and model governance. Work with domain experts to make validation, stability and fairness checks practical and reviewable.\n\nLead technical discussions, review code, unblock engineers and keep the client informed about progress, risks and architectural decisions.\n\nAssess where natural-language or LLM-assisted analytics would add value, without losing focus on trustworthy data, robust models and useful products.\n\nWhat we are looking for\nA track record of designing and delivering production data or ML systems, with ownership extending beyond prototypes and architecture diagrams.\n\nStrong hands-on Python and SQL. You should be comfortable investigating a dataset, reviewing modelling code and implementing critical parts of the solution yourself.\n\nPractical MLOps experience: reproducible pipelines, model and data versioning, testing, deployment, monitoring and the operational consequences of model updates.\n\nExperience with cloud data platforms and modern warehouses. Snowflake experience is particularly relevant; you should be able to reason about data access, performance, cost and deployment constraints.\n\nAn understanding of model evaluation, calibration, data leakage, changing populations and the difference between model quality and system reliability.\n\nThe ability to work through incomplete documentation and inconsistent business definitions, and turn findings into maintainable code and clear documentation.\n\nStrong client-facing communication in English. You can explain trade-offs to non-technical stakeholders, constructively challenge a requirement and take responsibility for the resulting decision.\n\nExperience leading a small technical team while remaining actively involved in implementation.\n\nUseful additional experience\nCredit-risk, lending or servicing analytics, including PD, LGD, ECL, prepayment or portfolio stress testing.\n\nRegulated financial-services delivery and model governance.\n\nStreamlit, Azure ML, semantic data layers or analytics applications built on Snowflake.\n\nConfigurable ML products serving multiple portfolios or clients.\n\nEvaluated natural-language analytics, text-to-SQL or LLM-assisted workflows.\n\nCurrent technical environment\nSnowflake, SQL, Python, Streamlit and an Azure ML environment. The team also uses AI-assisted development tools. You will help evolve the architecture based on the product’s needs rather than introduce a predetermined stack.\nWhat we would like to discuss\nA production ML or analytics system you personally helped build, including the architecture decisions and code you owned.\n\nHow you would adapt a model and its calibration for a new portfolio while preserving reproducibility, access boundaries and validation.\n\nA time you challenged a business or technical assumption, proposed an alternative and delivered a better outcome.","description_format":"text","description_chars":5191,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Upper-Intermediate (B2)","optional":false}]},"benefits":[],"hiring_locations":[{"name":"Bulgaria","iso":"BG","kind":"country"},{"name":"Cyprus","iso":"CY","kind":"country"},{"name":"Czech Republic","iso":"CZ","kind":"country"},{"name":"Hungary","iso":"HU","kind":"country"},{"name":"Italy","iso":"IT","kind":"country"},{"name":"Poland","iso":"PL","kind":"country"},{"name":"Romania","iso":"RO","kind":"country"},{"name":"Serbia","iso":"RS","kind":"country"},{"name":"Spain","iso":"ES","kind":"country"},{"name":"Ukraine","iso":"UA","kind":"country"},{"name":"Albania","iso":"AL","kind":"country"},{"name":"Estonia","iso":"EE","kind":"country"},{"name":"Greece","iso":"GR","kind":"country"},{"name":"Lithuania","iso":"LT","kind":"country"},{"name":"Malta","iso":"MT","kind":"country"},{"name":"Moldova","iso":"MD","kind":"country"},{"name":"North Macedonia","iso":"MK","kind":"country"},{"name":"Portugal","iso":"PT","kind":"country"},{"name":"Slovakia","iso":"SK","kind":"country"},{"name":"Slovenia","iso":"SI","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["AI Agents","Financial AI","AI Consulting & Integration"],"lifecycle":[{"event":"open","at":"2026-10-21T10:13:53Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":3,"expected_fill_days":68,"reasons":["conf:2","win:early"],"computed_at":"2026-10-25T05:49:26Z"},"pay":null,"html_url":"https://alion.io/job/neurons-lab-forward-deployed-architect-credit-analytics-ml-platforms","json_url":"https://alion.io/job/neurons-lab-forward-deployed-architect-credit-analytics-ml-platforms.json","meta":{"generated_at":"2026-10-25T21:06:24Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":29890,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-26T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4957},"rest":"https://alion.io/mcp/rest/get_company?id=4957"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fneurons-lab-forward-deployed-architect-credit-analytics-ml-platforms"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fneurons-lab-forward-deployed-architect-credit-analytics-ml-platforms"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fneurons-lab-forward-deployed-architect-credit-analytics-ml-platforms"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/neurons-lab-forward-deployed-architect-credit-analytics-ml-platforms\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fneurons-lab-forward-deployed-architect-credit-analytics-ml-platforms"}]}