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Staff Machine Learning Engineer

Staff Machine Learning Engineer

Cape Analytics, Inc.Bayern, Germany
Vor 2 Tagen
Stellenbeschreibung

A BIT ABOUT US

At CAPE, we pioneered the creation of property intelligence analytics through computer vision, machine learning, and geospatial imagery.

Property intelligence from CAPE allows insurance carriers to elevate their underwriting workflows, which consider a multitude of risk factors that determine each policy’s eligibility and price. CAPE’s low-latency APIs feed risk-relevant data into consumer shopping interfaces, programmatic underwriting workflows, and insurance pricing models. Our risk intelligence web portal provides a deep view into property-level risk for underwriters. CAPE’s products improve our clients’ underwriting efficiency and effectiveness and enable them to deliver superior experiences to their policyholders.

CAPE’s solutions have been adopted by leading insurance carriers across the U.S., Canada, and Australia...but we are just getting started. Over the past 10 years, we have constructed a risk analytics platform purpose-built for deep learning. Going forward, we set out to solve an even larger share of the problem, leveraging a radically expanded array of input data sources and advanced machine learning technologies.

THE OPPORTUNITY :

We are looking for a Staff Machine Learning Engineer with a passion for building practical, robust, and scalable machine learning solutions, and interacting cross-functionally with a variety of teams. Specifically, you will be responsible for improving and extending our core product offering. You will gain expertise in the full model development stack, from ground truth generation to in-depth model performance and proof-of-value analysis for our clients. You will also contribute to product research, ensuring that our machine learning solutions meet high standards while delivering maximum value to our clients.

At the staff level, you will also be responsible for assessing the feasibility of novel ML solutions (whether our engineers can build what is needed with the time, skills, and technology available), overseeing the work of others, and participating in product roadmap planning.

This opportunity can be 100% Remote!

Our Munich office is available for optional in-person team collaboration.

WITHIN 1 MONTH, YOU’LL :

  • Understand the Context : Gain a clear understanding of CAPE’s role in insurance analytics, its mission, values, and how our technology empowers clients.
  • Onboard and Familiarize : Complete onboarding, familiarize yourself with CAPE’s technical stack, and review key documentation, including existing models and workflows.
  • Build Relationships : Establish connections with your immediate team and key cross-functional stakeholders.
  • Contribute to Well-Defined Tasks : Begin contributing to smaller, well-defined tasks or analyses to understand workflows, tools, and expectations.
  • Explore Data Basics : Conduct basic data exploration to identify patterns, distributions, and data quality issues.

WITHIN 3 MONTHS, YOU’LL :

  • Conduct Advanced Analysis : Analyze data to uncover deeper insights, create compelling visualizations, and translate findings into actionable recommendations.
  • Refine Models : Begin improving and fine-tuning machine learning models based on identified business needs and existing performance benchmarks.
  • Explore New Data Sources : Identify, assess, and validate new internal or external data sources to enhance models or analyses.
  • Lead Smaller Projects : Take ownership of smaller initiatives, ensuring alignment with CAPE’s priorities and governance standards.
  • Share Knowledge : Actively mentor and share expertise with team members, contributing to the organization’s knowledge base.
  • Participate Strategically : Engage in project planning and prioritization, offering insights to guide technical and business decisions.
  • Evaluate Design Trade-Offs : Thoughtfully assess design changes, balancing technical feasibility, model accuracy, and business impact.

    • WITHIN 6 MONTHS, YOU’LL :

  • Deliver Impactful Results : Lead the development and deployment of complex models or systems that drive measurable improvements in CAPE’s analytics capabilities.
  • Create Accessible Documentation : Create comprehensive, accessible documentation of findings, methodologies, and systems for both technical and non-technical audiences.
  • Address Systemic Challenges : Identify inefficiencies in processes, workflows, or systems, and implement solutions with long-term impact.
  • Mitigate Risks : Proactively identify risks in model development or deployment and implement mitigation strategies.
  • Drive Innovation : Design, validate, and implement new approaches, algorithms, or models to solve complex business challenges.
  • Influence Planning : Contribute meaningfully to quarterly and strategic planning by proposing high-impact projects and reviewing others’ ideas.
  • Establish Leadership : Build trust and credibility across teams through clear communication, technical excellence, and collaboration.

    • THE SKILL SET :

  • PhD in a STEM field with 3 years of hands-on industry experience, or a Master’s degree in a STEM field with 7+ years of hands-on industry experience.
  • Expert written and verbal communication skills, with the ability to understand and articulate business requirements and objectives to both technical and non-technical stakeholders.
  • Advanced expertise of statistical techniques, including hypothesis testing, statistical sampling, significance testing, statistical inference, maximum likelihood estimation, and experimental design, among others.
  • Advanced expertise of supervised and unsupervised algorithms and their implementations, machine learning concepts including regularization, learning curves, optimizing hyperparameters, cross-validation, among others.
  • Advanced expertise with deep learning for computer vision.
  • Advanced expertise in Python programming or other scripting languages including relevant libraries like numpy, pandas, SciPy, matplotlib.
  • Advanced expertise of tools in the modern ML stack such as Spark, Jupyter, Docker, Git and cloud computing on AWS or GCP.
  • Advanced expertise in building data tools for ETL, extracting data from SQL and NoSQL databases, and data analysis.
  • Advanced expertise in building meaningful data visualizations.
  • Experience with GIS systems is preferred.
  • Experience in mentoring junior team members and leading projects.
  • Ability to travel 1-2 times annually for company / team events.

    • THE TEAM :

    You will work with some of the smartest data scientists and machine learning engineers in the industry! They are passionate about the work they do, and have collectively built the industry’s leading AI / Analytics product. Success only comes with great team culture, collaboration, open communication and hard work. These are the qualities that you will experience and enjoy at CAPE.

    WE BELIEVE :

  • Talent is critical, but best when tempered with humility
  • Self-motivation leads to the best outcomes
  • Open, direct communication is a sign of respect
  • Teamwork drives success
  • Having fun together is an important part of the job!

    • COMPENSATION & BENEFITS :

    Cape Analytics believes in creating a more equitable environment for everyone, and is committed to standing against wage gap disparities that are widened by limited pay transparency.

    Positions at Cape may also include stock options, bonus opportunities, and / or variable incentive pay (commissions) to supplement your base earnings. Additionally, Cape offers top-notch insurance options and competitive benefits- such as unlimited PTO, company outings, remote work capabilities and more!

    The pay range for this role is :

    100,433 - 167,388 EUR per year(Munich)

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