Senior Data Scientist
Company: CAPE Analytics
Location: Mountain View
Posted on: July 31, 2022
Job Description:
Cape Analytics provides instant property intelligence for
buildings across the United States. Cape Analytics enables insurers
and other property stakeholders to access valuable property
attributes at time of underwriting, with the accuracy and detail
that traditionally required an on-site inspection, but with the
speed and coverage of property record pre-fill. Founded in 2014,
Cape Analytics is backed by leading venture firms and innovative
insurers and is comprised of computer vision, data science, and
risk analysis experts.THE OPPORTUNITYAs a Senior Data Scientist on
CAPE's Data Science team, you'll collaborate with Data Scientists,
Computer Vision/Machine Learning Engineers, Data Engineers, and
members across Software Engineering, Product, and Sales teams to
build robust, scalable machine learning models for identification
and annotation of the built world. Additionally, you will develop
expertise in ground truth generation, model performance analysis,
iterative model development, and unsupervised mapping of the
feature space to bring scientific rigor, scalability, and robust
performance to our core product offerings.As a senior member of the
team, you will also oversee the work of other data scientists in
the team and work with Product Managers to plan the roadmap for the
team.CAPE's insurance solutions have been adopted by leading
carriers across the U.S., Canada, and Australia...but we are just
getting started. Over the past 6 years, we've constructed an
analytics platform purpose-built for deep learning. On the heels of
our recent $44 million Series C financing, we're growing rapidly.
In CAPE's next phase, we're setting out to solve a larger share of
the problem, leveraging a radically expanded array of input data
sources and advanced machine learning technologies.THE TECH
STACKCAPE leverages all available tools and technologies to build
our best-in-class tech-stack, which affords us flexibility of
fast-deployments, along with the stability to support aggressive
SLAs for critical-path client APIs and applications. We build our
models using Pytorch and Tensorflow, and leverage Python, Spark and
Postgres across our AWS-deployed cloud infrastructure.WITHIN 1
MONTH, YOU'LL
- Develop scientifically rigorous, creative methodologies to
continuously improve our machine learning models
- Incorporate machine learning and data-driven decisioning into
the core of our infrastructure
- Explore and mine new data sources that will help optimize and
validate our models
- Link model capabilities to market needs by customizing models,
designing and running validation studiesWITHIN 3 MONTHS, YOU'LL
- Start to assist in Sprint planning and Quarterly planning with
the team
- Contribute to design and automation of model training, model
post-processing and evaluation pipelines at scale
- Leverage the extensive data generated by Cape in addition to
data from external sources to generate structured knowledge about
our feature space
- Implement automated solutions for ensuring data quality and
delivery
- Contribute to peer mentorship, knowledge bases, and skills
transferWITHIN 6 MONTHS, YOU'LL
- Be primarily responsible for roadmap planning with Product team
along with Sprint planning and Quarterly planning
- Present your results internally and externally
- Defend your methodology and incorporate feedback from internal
teams as well as customers
- Improve model performance by identifying failure modes using
supervised and unsupervised learning techniques
- Ideate and implement data-driven methodologies to help scale
model performance across geographical, climatic, and temporal
dimensionsTHE SKILL SET
- PhD in a STEM field with 3 years of hands-on industry
experience or Masters in a STEM field with 5 years of hands-on
industry experience
- A background in the Finance or Real Estate sector is strongly
preferred. This includes familiarity with Real Estate data such as
MLS and other public record data, Mortgage Loans, Automated
Valuation Models, Asset Valuations, Cash Flow Analysis, Risk
Analysis etc.
- Solid knowledge of statistical techniques, including hypothesis
testing, statistical sampling, significance testing, statistical
inference, maximum likelihood estimation, and experimental design,
among others
- Mastery of, supervised and unsupervised algorithms and their
implementations, machine learning concepts including
regularization, learning curves, optimizing hyperparameters,
cross-validation, among others
- Advanced knowledge and significant programming experience in
Python programming or other scripting language including relevant
libraries like numpy, pandas, SciPy, matplotlib
- Familiarity with the Linux environment including shell
scripting, Git and tools for reproducibility (e.g. virtual
environments, Docker)
- Demonstrated expertise in building data tools for ETL and data
analysis
- Experience in building meaningful data visualizations using at
least one scripting-based visualization tool such as matplotlib,
d3.js or bokeh
- Nice to haves: Experience designing data schemas and extracting
data from SQL and NoSQL databases. Experience with GIS systems.
Experience with modern data technologies, e.g. Spark, pytorch,
Jupyter Notebook, DockerExperience with cloud computing on AWS or
GCPTHE TEAMYou will work with some of the smartest data scientists
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, camaraderie,
open communication and hard work. These are the qualities that you
will experience and enjoy at Cape.
Keywords: CAPE Analytics, Mountain View , Senior Data Scientist, Accounting, Auditing , Mountain View, California
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