<p>Location: Austin TX or Toronto ON or Washington DC</p><br/><p>Employment Type: Full-time</p><br/><p>Team: Data Science</p><br/><div><b style="font-size: 10pt">About Cerebri AI</b></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><span style="font-size: 10pt">Cerebri AI CVX platform uses the best Artificial Intelligence ( AI ), Operation Research ( OR ), and software to provide what is required in our digital age: value a customer's commitment to a brand and related products. It then uses these insights to then drive the selling of product and services. We use AI to answer the fundamental questions of the digital age: Who talks to the customer? Who understands the customer? How do we do this at scale when we have millions of customers?</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><span style="font-size: 10pt">Cerebri AI CVX platform includes a streaming capable AI software pipeline that processes data intake thru to producing insights and actions &amp; presenting them via our APIs, in our customers' systems, or our UX. One customer journey ( CJ ) per customer means all models targeting CX and revenue KPIs and related next best offers ( NBOs ) use the same journeys.</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><span style="font-size: 10pt">We work with companies selling to over 200 million consumers and have 26 patents filed ( 8 granted ) on the Cerebri CVX platform. We now have 35 employees in three offices in Austin, Toronto, and Washington DC ( well around three offices ). Over 80% of the staff are in technical roles in data science and software engineering.&nbsp;</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><span style="font-size: 10pt">How do we do this? We hire the best data scientists, mathematicians, and software developers and work as a cross-disciplinary team/gang/clan. We work hard, laugh hard, and impress our peers and clients. Because we can. And because we want to. To learn more, visit&nbsp;</span><a href="http://www.cerebri.com/" style="font-size: 10pt" class="postings-link">cerebriai.com</a><span style="font-size: 10pt">. In the meantime, if you think you have what it takes, give us a spin and upload resume.</span></div><div><span style="font-size: 10pt">How do we do this? We hire the best data scientists, mathematicians, and software developers and work as a cross-disciplinary team/gang/clan. We work hard, laugh hard, and impress our peers and clients. Because we can. And because we want to. To learn more, visit&nbsp;</span><a href="http://www.cerebri.com/" style="font-size: 10pt" class="postings-link">cerebriai.com</a><span style="font-size: 10pt">. In the meantime, if you think you have what it takes, give us a spin and upload resume.</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><b><span style="font-size: 10pt">"Cerebri AI was recognized as 2019 Cool Vendor for Customer Journey Analytics by Gartner."</span></b></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><b style="font-size: 10pt">The ideal candidate</b></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><span style="font-size: 10pt">The ideal candidate is adept at leveraging large data sets to find patterns and using modelling techniques to test the effectiveness of different actions. S/he must have strong experience using various data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms, creating/running simulations, and testing its real-time implication. S/he must be comfortable working with a wide range of stakeholders and functional teams, trading off design to help others.&nbsp;</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><b style="font-size: 10pt">Responsibilities for Senior/Principal Data Scientist</b></div><div><b style="font-size: 10pt">&nbsp;</b></div><div><span style="font-size: 10pt">Design, develop, test, advocate, evangelize and build data-driven modeling approaches</span></div><div><span style="font-size: 10pt">Assess the effectiveness and performance of modeling and data enhancement techniques</span></div><div><span style="font-size: 10pt">Perform feature analysis</span></div><div><span style="font-size: 10pt">Develop ontology for key market segments</span></div><div><span style="font-size: 10pt">Develop outcome/event taxonomy for key business models</span></div><div><span style="font-size: 10pt">Coordinate with different functional teams to implement data engineering, models and monitor outcomes</span></div><div><span style="font-size: 10pt">Build utility code and handle miscellaneous support tasks&nbsp;</span></div><div><span style="font-size: 10pt">Documenting projects and maintaining project documentation</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><b style="font-size: 10pt">Qualifications</b></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Strong problem-solving skills with an emphasis on product development</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">6+ year experience working with and creating data architectures</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Experience with artificial intelligence, natural language processing, machine learning</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Excellent understanding of machine learning techniques: Supervised/Unsupervised/semi-supervised Learning, SVM, Tree-based Methods, Neural Networks, Naive Bayes, k-NN, ensemble methods, CNN, RNN, NLP, Feature Engineering, hyperparameters optimization, data visualization&nbsp;</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, 0-hypothesis, Regularization)</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Experience using statistical computer languages (Python, SQL, etc.) and conventional data science toolkits, such as PANDAS, Weka, NumPy, MATLAB</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Experience with NoSQL databases</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Excellent written and verbal communication skills</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Project management</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">A drive to learn and master new technologies and techniques</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><b style="font-size: 10pt">Tools we use</b></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Confluence</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">JIRA</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Spark</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Azure, AWS, Kubernetes</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Python, Scala</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Keras, Scikit-learn, PANDAS, Numpy</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Bit bucket, GitHub</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Jupyter Notebook</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Postgress, Parquet</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">JavaScript, airflow, Pulsar</span></div><div><span style="font-size: 10pt">&nbsp;</span></div><div><b style="font-size: 10pt">Nice to haves</b></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Ph.D. in operations research, applied statistics, data mining, machine learning, physics or a related quantitative discipline</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Experience in operations research, applied statistics, algorithmic complexity, RDS</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Experience with time Series, econometrics</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Experience with streaming systems</span></div><div><span style="font-size: 10pt">·</span><span style="font-size: 7pt">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span><span style="font-size: 10pt">Experience with Object-oriented modeling/MVC design patterns</span></div><div><br></div><div><span style="font-size: 10pt">How do we do this? We hire the best data scientists, mathematicians, and software developers and work as a cross-disciplinary team/gang/clan. We work hard, laugh hard, and impress our peers and clients. Because we can. And because we want to. To learn more, visit&nbsp;</span><a href="http://www.cerebri.com/" style="font-size: 10pt" class="postings-link">cerebriai.com</a><span style="font-size: 10pt">. In the meantime, if you think you have what it takes, give us a spin and upload resume.</span></div><div><br></div><div><br></div><div>Specify your location preference</div>

Location: Austin TX or Toronto ON or Washington DC

  

Employment Type: Full-time

  

Team: Data Science

  

 **About Cerebri AI**



Cerebri AI CVX platform uses the best Artificial Intelligence ( AI ),
Operation Research ( OR ), and software to provide what is required in our
digital age: value a customer's commitment to a brand and related products. It
then uses these insights to then drive the selling of product and services. We
use AI to answer the fundamental questions of the digital age: Who talks to
the customer? Who understands the customer? How do we do this at scale when we
have millions of customers?



Cerebri AI CVX platform includes a streaming capable AI software pipeline that
processes data intake thru to producing insights and actions & presenting them
via our APIs, in our customers' systems, or our UX. One customer journey ( CJ
) per customer means all models targeting CX and revenue KPIs and related next
best offers ( NBOs ) use the same journeys.



We work with companies selling to over 200 million consumers and have 26
patents filed ( 8 granted ) on the Cerebri CVX platform. We now have 35
employees in three offices in Austin, Toronto, and Washington DC ( well around
three offices ). Over 80% of the staff are in technical roles in data science
and software engineering.



How do we do this? We hire the best data scientists, mathematicians, and
software developers and work as a cross-disciplinary team/gang/clan. We work
hard, laugh hard, and impress our peers and clients. Because we can. And
because we want to. To learn more, visit
[cerebriai.com](http://www.cerebri.com/). In the meantime, if you think you
have what it takes, give us a spin and upload resume.

How do we do this? We hire the best data scientists, mathematicians, and
software developers and work as a cross-disciplinary team/gang/clan. We work
hard, laugh hard, and impress our peers and clients. Because we can. And
because we want to. To learn more, visit
[cerebriai.com](http://www.cerebri.com/). In the meantime, if you think you
have what it takes, give us a spin and upload resume.



 **"Cerebri AI was recognized as 2019 Cool Vendor for Customer Journey
Analytics by Gartner."**



 **The ideal candidate**



The ideal candidate is adept at leveraging large data sets to find patterns
and using modelling techniques to test the effectiveness of different actions.
S/he must have strong experience using various data mining/data analysis
methods, using a variety of data tools, building and implementing models,
using/creating algorithms, creating/running simulations, and testing its real-
time implication. S/he must be comfortable working with a wide range of
stakeholders and functional teams, trading off design to help others.



 **Responsibilities for Senior/Principal Data Scientist**

 ** **

Design, develop, test, advocate, evangelize and build data-driven modeling
approaches

Assess the effectiveness and performance of modeling and data enhancement
techniques

Perform feature analysis

Develop ontology for key market segments

Develop outcome/event taxonomy for key business models

Coordinate with different functional teams to implement data engineering,
models and monitor outcomes

Build utility code and handle miscellaneous support tasks

Documenting projects and maintaining project documentation



 **Qualifications**



·       Strong problem-solving skills with an emphasis on product development

·       6+ year experience working with and creating data architectures

·       Experience with artificial intelligence, natural language processing,
machine learning

·       Excellent understanding of machine learning techniques:
Supervised/Unsupervised/semi-supervised Learning, SVM, Tree-based Methods,
Neural Networks, Naive Bayes, k-NN, ensemble methods, CNN, RNN, NLP, Feature
Engineering, hyperparameters optimization, data visualization

·       Knowledge of advanced statistical techniques and concepts (regression,
properties of distributions, statistical tests, 0-hypothesis, Regularization)

·       Experience using statistical computer languages (Python, SQL, etc.)
and conventional data science toolkits, such as PANDAS, Weka, NumPy, MATLAB

·       Experience with NoSQL databases

·       Knowledge of professional software engineering practices and best
practices for the full software development life cycle, including coding
standards, code reviews, source control management, build processes, testing,
and operations

·       Excellent written and verbal communication skills

·       Project management

·       A drive to learn and master new technologies and techniques



 **Tools we use**

·       Confluence

·       JIRA

·       Spark

·       Azure, AWS, Kubernetes

·       Python, Scala

·       Keras, Scikit-learn, PANDAS, Numpy

·       Bit bucket, GitHub

·       Jupyter Notebook

·       Postgress, Parquet

·       JavaScript, airflow, Pulsar



 **Nice to haves**

·  

·       Ph.D. in operations research, applied statistics, data mining, machine
learning, physics or a related quantitative discipline

·       Experience in operations research, applied statistics, algorithmic
complexity, RDS

·       Experience with time Series, econometrics

·       Experience with streaming systems

·       Experience with Object-oriented modeling/MVC design patterns

  

How do we do this? We hire the best data scientists, mathematicians, and
software developers and work as a cross-disciplinary team/gang/clan. We work
hard, laugh hard, and impress our peers and clients. Because we can. And
because we want to. To learn more, visit
[cerebriai.com](http://www.cerebri.com/). In the meantime, if you think you
have what it takes, give us a spin and upload resume.

  

  

Specify your location preference

