{"id":2294933,"url":"https://alion.io/job/purpose-staff-data-scientist","title":"Staff Data Scientist","company":{"id":1526678,"name":"Purpose","domain":"purpose.ca","url":"https://alion.io/company/purpose-ca","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Montreal, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":78000,"max_usd":157000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":10},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AI Agents","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-11T18:39:35Z","employer_posted_date":null,"last_verified_at":"2026-10-11T18:39:35Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Purpose Unlimited is an independent financial services company with an unrelenting focus on customer-centric innovation, delivered through technology-driven solutions. Led by entrepreneur Som Seif, the company is developing a diversified product platform aimed at addressing historically underserved segments of the market. Purpose Unlimited’s businesses include Purpose Investments, Advisor Solutions by Purpose, and Driven.\nVacancy Status: This is for a current vacancy\nJob Description Who you are Customer behavior is a signal. Most companies collect it. Few know how to read it. You will be one of the early data science hires shaping how Purpose understands the clients on our wealth platform — and how the platform responds to what we learn. You'll build the measurement architecture, behavioral models, and causal infrastructure that connects product decisions to client outcomes. Not what looks like it works. What actually does. This is a foundational role at a foundational moment. The intelligence layer you build will shape how Purpose designs, measures, and evolves its platform for years — and increasingly, how our AI systems understand and serve the clients who depend on us. You're an engineer as much as a scientist — you own the work from raw event data to deployed system, and you hold yourself accountable for whether it changed how the business operates. What AI does so you don't have to\n\nRecurring insight generation — automated analytics workflows run on schedule with defined guardrails. You design the system and own the governance; you don't write the weekly summary.\n\nBoilerplate feature engineering — AI coding assistants accelerate pipeline construction from event data. You define what to build and review what the tools produce.\n\nFirst-pass segmentation refreshes — classification and scoring jobs re-run automatically. You set the standards and monitor for drift, you don't rerun the job.\n\nStandard visualization and reporting — AI tools increasingly generate monitoring views from structured data. You define what signals matter; the generation is handled.\n\nWhat only you can do\nDetermine what is worth measuring — in a platform generating thousands of behavioral signals, the most valuable judgment is deciding which three metrics actually reflect client value and which are vanity.\n\nPush back on attribution that flatters — AI systems generate correlations at scale. You are the person who asks whether the relationship is causal, whether the experiment is valid, and whether the conclusion will hold when the business acts on it.\n\nTranslate behavioral reality into a measurable operating model — starting from how clients actually make financial decisions, not from how the product team assumes they do.\n\nDesign AI analytics systems with the rigor of a statistician — evaluating LLM-generated insights with the same calibration and drift standards you apply to your own models.\n\nBuild the institutional trust that makes product and business leaders act on quantitative findings, including findings they didn't want.\n\nWhat you will own\nThe client intelligence architecture: the measurement model that maps how clients discover, onboard, activate, and engage with Purpose's wealth platform — with FOMs that connect platform activity to real client outcomes.\n\nBehavioral models that change decisions: client segmentation, lifecycle classification, churn prediction, propensity scoring, and behavioral clustering — validated against real outcomes and governed for drift.\n\nCausal measurement with discipline: experiment design and analysis, causal inference when experiments aren't possible, and a consistent standard for what counts as evidence that a product or AI intervention actually worked.\n\nAgentic analytics governance: you set the standards for what AI-generated insight requires human review, what guardrails govern automated outputs, and how the intelligence layer stays accurate and auditable in a regulated environment.\n\nWhat you must bring\nDeep fluency in Python and SQL — owning work end-to-end from raw event data to deployed software, with production-grade testing and documentation standards.\n\nProven experience building and evaluating predictive models in production-like settings: classification, survival models, segmentation, scoring, calibration, and cost-sensitive decision frameworks.\n\nApplied causal inference — A/B testing, matching/propensity, diff-in-diff, regression discontinuity. You know the difference between a valid experiment and a flattering one.\n\nExperience in a regulated industry (financial services, healthcare, or equivalent) — you treat data access controls, model auditability, and responsible use of customer data as core professional standards.\n\nWhat will set you apart\nYou've been early on a data science or analytics team and built measurement and modeling foundations before the playbook existed — you know what it means to make something from scratch that others depend on.\n\nYou have experience evaluating LLMs or AI-generated outputs with statistical rigor: calibration, drift detection, bias assessment. You apply the same skepticism to AI outputs that you apply to your own models.\n\nYou've used AI-assisted development tools (GitHub Copilot, Claude Code, Cursor, or equivalent) as a genuine productivity multiplier in data science workflows.\n\nYou have applied behavioral economics or behavioral finance principles to how you designed metrics or interpreted client behavior — you think about why clients make financial decisions, not just what they do.\n\nWhat success looks like in your first year\n\nA measurement architecture is live — FOMs that connect platform activity to client outcomes are defined, instrumented, and being used by product and business leaders to make decisions they couldn't make before.\n\nAt least two behavioral models are in production — churn prediction, propensity scoring, or lifecycle classification — with monitoring, documentation, and governance that any engineer on the team can maintain.\n\nCausal measurement is the standard — at least one major product or AI intervention has been evaluated with a valid causal method, and the findings have changed how the team approaches attribution.\n\nThe AI analytics layer has governance — the standards for what AI-generated insight requires human review, and what guardrails govern automated output, are defined, documented, and in use.\n\nYou've become the person that product and business leaders bring their hardest measurement questions to — because they trust that what you tell them reflects reality, including when reality is inconvenient.\n\nEvery role at Purpose is assessed against our five values:\n\nInnovation – You bring new ideas, challenge the status quo, and find better ways of building. You don’t wait for permission to experiment.\n\nCourage – You speak up when something isn’t working, take difficult stands on technical quality, and act with conviction even when it’s uncomfortable.\n\nOwner’s Mindset – You take full accountability for your squad’s outcomes. You treat the platform, the team, and the business as your own.\n\nClient Focus – You place client outcomes at the center of every architectural and delivery decision.\n\nWinning Through Individual and Collective Growth – You invest in your own development and actively contribute to the growth of every engineer around you.\n\nWhy should you join us?\nWe are one of Canada's Top Small & Medium Employers' 2023, 2024, 2025 & 2026.\n\nWe believe in innovation and a vibrant culture - work for an innovative, people-first, financial services firm that values entrepreneurialism.\n\nWe believe in a flexible work structure – A flexible hybrid work model that empowers you to do your best work whether at home or the office.\n\nWe care about your rewards - Competitive compensation including equity program.\n\nWe care about your health – comprehensive group health and dental benefits and life insurance at little to no cost to you. We also offer a Lifestyle Spending Account for all your wellness needs.\n\nWe care about your quality of life - flexible paid time-off policy with unlimited vacation days, and flexible sick and mental health days.\n\nWe care about your family - Paid parental leave for eligible employees with a top-up.\n\nWe care about your future – Generous Group RRSP matching and an optional TFSA program.\n\nWe care about your development – We offer training opportunities and tuition support year-round.\n\nPurpose Unlimited is an equal employer and we are dedicated to fostering an inclusive and barrier-free work environment for all employees and candidates. We encourage all qualified candidates to apply and if accommodation is required during any stage of the recruitment process, please contact any member of the People & Culture team at . We thank all applicants for their interest; however, only those selected for interviews will be contacted. Our work philosophy is a hybrid model allowing for flexibility and collaboration. Applicants must be legally entitled to work in Canada. Immigration sponsorship is not offered for this role. We may use artificial intelligence technology to assist in screening, assessing, or selecting applicants for this position. Final hiring decisions are made by qualified human reviewers.\nOriginally posted on Himalayas","description_format":"text","description_chars":9283,"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":[]},"benefits":["Equity","Flexible schedule","Hybrid work","Life insurance","Parental leave"],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Services"],"lifecycle":[{"event":"open","at":"2026-10-11T20:32:15Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":30,"reasons":["seen:0","win:early"],"computed_at":"2026-10-12T06:55:09Z"},"pay":null,"html_url":"https://alion.io/job/purpose-staff-data-scientist","json_url":"https://alion.io/job/purpose-staff-data-scientist.json","meta":{"generated_at":"2026-10-12T18:46:37Z","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":"assistant_verified","counted_by":"address","units_charged":1,"used_today":3886,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"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":1526678},"rest":"https://alion.io/mcp/rest/get_company?id=1526678"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpurpose-staff-data-scientist"},{"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%2Fpurpose-staff-data-scientist"},{"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%2Fpurpose-staff-data-scientist"},{"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/purpose-staff-data-scientist\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpurpose-staff-data-scientist"}]}