CAREERSFORGE / YOUR NEXT MOVE
Ignis Your Career Coach & Workspace
See what you’ve practiced, what your resume demonstrates, and what to work on next.
Your next career move starts here
Your free AI career coach. Choose a goal, work through your next step, and return to review your progress.
Try it as a guest. Save Progress creates an account for your recorded activities and conversation history.
Readiness · Getting started
Activities recorded · 0
PRIVATE, IN-BROWSER TOOL
Decode a Rejection Email
Paste only what you’re comfortable reviewing. This tool matches common wording in your browser; it does not save the email, send it to AI, or know why the employer made its decision.
Wording found in the email
Possible meaning — not a fact about this decision
Three practical next steps
60-SECOND CLARITY ROUND
Spot the Red Flag
These are illustrative practice snippets, not quotes from real employers. A phrase alone does not prove a workplace is harmful; use it as a prompt to ask for specifics.
Choose the wording that needs a follow-up question. Clear scope, documented onboarding, and reasonable boundaries are useful context too.
Use the explanation as a conversation starter, not as a verdict on a company.
Quick Start: How Ignis Works
-
1. Build or Scan
Create or review a resume.
-
2. Train Your Focus
Try a short exercise and review your practice score.
-
3. Consult Ignis
Use your recorded results to plan a next step.
Your next step with Ignis
Ask Ignis to connect your recorded results and suggest one practical next step.
Your next step starts here
Your performance radar unlocks after your first recorded activity. Complete a 2-minute mock interview or scan a resume to generate your report.
Career Health Radar
Complete a resume review or a Brain Training session to see your results here.
Readiness labels summarize recorded practice. They are planning cues, not hiring predictions or a measure of job suitability.
Strengths and priorities
Complete a resume review to see strengths and improvement priorities.
Open Interview Practice →Top matched roles
Compare your evidence with a role in Job Radar to calculate a match.
Activity mix
Your next step starts here
Your practice dashboard unlocks after your first recorded activity. Begin with a short interview or resume review, then explore your daily sprint and training.
Daily Career Sprint
Daily Confidence Pill
Loading today’s practical career prompt…
Optional: breathe in for 4 seconds, then out for 4.
TODAY’S CHALLENGE
One small practice, chosen for today
Build a little momentum with a short reasoning exercise or a job-description clarity round.
Brain Training
No synced game results yet.
Skill scores average the latest result from each played exercise in that category. Open a category to see each exercise.
YOUR ROLE, YOUR NEXT MOVE
Job Radar
Explore published opportunities, filter by your priorities, and open a listing to review its requirements and apply. Choose “Open match details in Workspace” to compare your analyzed resume with the role and plan your next step.
Tool preparation
0%
Loading recorded preparation…
Open roles
1,467 jobs found · Showing 1–12
ROLE MATCH
Applied Scientist at Upstart
Review your resume for this role →
{"title":"Applied Scientist at Upstart","requirements":["2+ years of experience conducting machine-learning, statistical-modeling, or applied quantitative research in an academic or industry setting.","Experience with marketplace optimization, particularly where pricing or offer decisions are central.","Experience with causal machine-learning methods or treatment-effect modeling.","Experience with supervised learning, model evaluation, and feature engineering, especially with large or complex datasets."],"description":"About Upstart\nAt Upstart, we\u2019re united by a mission that matters: to radically reduce the cost and complexity of borrowing for all Americans. Every day, we bring creativity, experimentation, and advanced AI to reshape access to credit, helping millions move forward financially with clarity and confidence.\nAs the leading AI lending marketplace, we partner with banks and credit unions to expand access to affordable credit through technology that\u2019s both radically intelligent and deeply human. Our platform runs over one million predictions per borrower using more than 3,000 signals, powering smarter, fairer decisions for millions of customers. But the numbers only hint at the impact. Every idea, every voice, and every contribution moves us closer to a world where credit never stands between people and their financial progress.\nWe\u2019re proudly digital-first, giving most Upstarters the flexibility to do their best work from wherever they thrive, alongside teammates across 80+ cities in the US and Canada. Digital-first doesn\u2019t mean distant. We\u2019re intentional about in-person connection through team onsites, planning sessions, and moments that spark creativity and trust. And whether you choose to work primarily from home or collaborate in-person from one of our offices in Columbus, Austin, the Bay Area, or New York City, you\u2019ll have the support to work in the way that works best for you.\nIf you\u2019re energized by tackling meaningful problems, excited to innovate with purpose, and motivated by work that truly matters, we\u2019d love to hear from you.\nThe Team\nUpstart\u2019s Partnerships team helps drive customer acquisition and originations through partner offers. The team is focused on improving how offers are optimized across the customer journey.\nAs the Applied Scientist on the Partnerships team, you\u2019ll use causal inference, experimentation, and machine learning to help determine which offers are most likely to support customer conversion. You\u2019ll take on a greenfield optimization opportunity, moving from research and measurement to production-ready models and decision strategies.\nHow you\u2019ll make an impact\n\nDevelop causal machine-learning models to optimize customer offers at different points in the funnel, from marketing-time decisions with limited information to decisions informed by customer activity on our site.\nAnalyze and interpret complex data, identify gaps in what we know, and design experiments to gather evidence for building and evaluating optimization models.\nMeasure the impact of offer changes with statistically rigorous experiments and evaluations.\nTranslate research and results into clear recommendations, decision strategies, and next steps for business and technical partners.\nBuild production-ready models and code for use in offer selection.\nPartner with Partnerships leadership, Product, Engineering, peer machine-learning teams, and model-risk partners to align on strategy, implementation, and methodology.\n\nMinimum Qualifications\n\nGraduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field.\n2+ years of experience conducting machine-learning, statistical-modeling, or applied quantitative research in an academic or industry setting.\nExperience applying causal inference methods and experimentation to real-world decisions in an applied-science or data-science context.\nApplied statistics, probability, and experimental-design expertise used to build or evaluate models or interventions.\nProduction-quality coding experience in Python, including data manipulation and algorithm implementation.\n\nPreferred Qualifications\n\nPhD in a quantitative field.\nExperience with marketplace optimization, particularly where pricing or offer decisions are central.\nExperience with causal machine-learning methods or treatment-effect modeling.\nExperience with supervised learning, model evaluation, and feature engineering, especially with large or complex datasets.\nExperience taking work from exploratory analysis and experimentation through production-model development while maintaining analytical rigor and model reliability.\nAbility to translate broad business problems into structured research questions and communicate complex findings as actionable recommendations.\n\nPosition location This role is available in the following locations: Remote\nTravel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions\u2019 cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.\n\n#LI-REMOTE\n#LI-Associate \nAt Upstart, your base pay is one part of your total compensation package. The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location\u2013with our \u201cdigital first\u201d philosophy, Upstart uses compensation regions that vary depending on location. Individual pay is also determined by job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.\nIn addition, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).\nUnited States | Remote - Anticipated Base Salary Range\n$141,500\u2014$196,000 USD\nWhat you\u0027ll love\nAt Upstart, our benefits for full-time employees are designed to support your health, financial well-being, family, and personal growth. Here\u2019s what you can expect:\n\nCompetitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly \nRetirement benefits to help you plan for the future, including a 401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually (USD in the US, CAD in Canada)\nEmployee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees (US only)\nComprehensive health coverage designed to support you and your family, including medical, dental, vision, and wellness resources for US and supplemental health coverage for Canada.\nHealth Savings Account contributions from Upstart for eligible plans (US only)\nIncome protection benefits, including life insurance and disability coverage for added financial security\nPaid time off, sick leave, and company holidays, in line with local requirements\nPaid family and parental leave to support caregiving and major life moments (duration varies by country)\nFamily-centered benefits to support fertility, parenthood, and caregiving needs\nEmployee Assistance Program (EAP) offering mental health support and life-centered resources\nFinancial wellness resources, including access to financial planning tools and a financial concierge service (US Only)\nAnnual wellness allowance to support your physical and emotional well-being and personal development, based on what matters most to you\nAnnual productivity allowance to invest in relevant tools and resources you need to do your best work, no matter where you work from\nConnection and community through team events, all-company updates, and employee resource groups (ERGs)\nOnsite perks, including catered lunches and fully stocked micro-kitchens when working from one of our offices in the Bay Area, Austin, Columbus, and New York City\n\nFor roles based in Canada, please note that we are not currently able to hire in Quebec.\nUpstart is a proud Equal Opportunity Employer. Just as we are dedicated to improving access to affordable credit for all, we are committed to inclusive and fair hiring practices.\nIf you require reasonable accommodation in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please email [email protected]\nhttps:\/\/www.upstart.com\/candidate_privacy_policy"}0%
Resume evidence match
Analyze your resume to calculate your match.
The percentage summarizes matching terms in the resume and role criteria. Review the requirements, experience level, qualifications, and application instructions before applying.
Analyze my resume →Signals found in your resume
Signals to review or strengthen
Review the listing criteria
- 2+ years of experience conducting machine-learning, statistical-modeling, or applied quantitative research in an academic or industry setting.
- Experience with marketplace optimization, particularly where pricing or offer decisions are central.
- Experience with causal machine-learning methods or treatment-effect modeling.
- Experience with supervised learning, model evaluation, and feature engineering, especially with large or complex datasets.
Application board
Sign in to track applications privately.