Posted on: February 24, 2021
The Kinesso Research & Development Team's mission is to produce
novel and disruptive solutions in the media, advertising, and
marketing technology space. We pursue this mission by identifying
key industry opportunities and trends and designing new algorithmic
tools using concepts from game theory, information theory,
probability & statistics, reinforcement learning, nonlinear
dynamics, and various other areas of mathematics, data science, and
technology, to extract commercial value. At any given time, we will
be developing two to four major projects with one- to two-year time
horizons and a small number of faster-cycle projects with a more
narrow focus. We are a small team whose existence consists mainly
of pushing at high-speed down a path while simultaneously drawing
the map for that path. In pursuing its mission, the Research &
Development Team constantly identifies new data sources from both
inside and outside the existing business and incorporates them into
local platforms for use in its projects. The R&D Data Engineer
will be responsible for efficiently architecting, building, and
maintaining (1) the data infrastructure to enable the R&D
Team's machine learning and data science specialists to build
applications that use this data, and (2) the application
infrastructure to optimize the R&D process and eventual handoff
of R&D tools for full productization elsewhere in the company.
The ideal candidate is an experienced data pipeline builder and
data wrangler who enjoys optimizing data systems and building them
from the ground up. They must be self-directed, comfortable working
in the presence of ambiguity, and confident enough to respond to
ambiguity by making a reasoned judgment, trying an optimal
approach, evaluating the success or failure of that approach, and
trying again if necessary.
- Create and maintain optimal data pipeline architecture,
assemble large, complex data sets that meet functional /
non-functional business requirements.
- Architect application infrastructure to contain and support
complex AI tools connecting reinforcement learning agents, deep
neural networks, proprietary algorithms, sensitive data sources,
and various external partners.
- Identify, design, and implement internal process improvements:
automating manual processes, optimizing data delivery, re-designing
infrastructure for greater scalability, etc.
- Build and manage the infrastructure required for optimal
automated extraction, transformation, and loading of data from a
wide variety of data sources using SQL, Snowflake, and AWS 'big
data' technologies, for use in speculative machine learning and AI
- Collaborate with data science and machine learning specialists
to produce analytics tools that utilize the data pipeline and
application infrastructure to provide actionable insights into
customer acquisition and implement closed-loop optimization of
media buying and customer acquisition systems.
- Integrate R&D Team tools with internal and external
platforms via API, FTP, and other means.
- Work with data science and machine learning/artificial
intelligence experts to strive for greater functionality in our
data systems. Desired Skills & Experience
- Experience with cloud and container systems including AWS cloud
services: EC2, EMR, RDS, S3, Redshift; Docker and Kubernetes
- Experience with object-oriented/object function scripting
languages: Python required; C++ a bonus, etc.
- Experience designing, programming, testing, and maintaining
reliable connections to RESTful APIs
- Experience creating database stored procedures and
- Experience architecting fast-cycle development for speculative
- Experience with reinforcement learning environments a
- Ability to communicate, collaborate and work in ambiguous and
unmapped contexts a necessity.
Keywords: Kinesso, Scranton , Data Engineer, Engineering , Walton, Pennsylvania
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