Responsibilities
- Understanding and worked with database systems.
- Understanding and worked with machine learning algorithms.
- Perform feature analysis.
- Develop ontology for key market segments.
- Develop outcome/event taxonomy for key business models.
- Build utility code and handle miscellaneous support tasks.
- Documenting software projects and maintaining project documentation.
- Working in a team environment as well as working alone.
Qualifications
- Experience with Big Data, artificial intelligence, natural language processing, machine learning and/or deep learning.
- Python programming skills with two (2) years or more of Python experience.
- Good verbal and written communication skills.
- 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.
- Master's degree or six (6) years related work experience delivering quality code on time.
Tools we use...
- Confluence
- JIRA
- Spark
- Azure
- Python
- Keras
- Scikit-learn
- Bit bucket
- Jupyter Notebook
- Scala
- MonetdB
- OrientDB
Nice to haves...
- Experience in some subset of the following: Java, R, Python, SQL, Scala, Spark.
- Ph.D. in operations research, applied statistics, data mining, machine learning, physics or a related quantitative discipline.
- Deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, supervised learning, recommendation and optimization algorithms.
About Cerebri AI
Cerebri AI provides AI and machine learning solutions to help enterprises grow top line revenues by giving them a 1:1 relationship with their customers. We do this by processing internal and external customer data, and by determining the dollar value a customer places on the “value” of a vendor, products, assets, etc. We also monetize a critical variable in any revenue situation, the customer’s ability to pay, so things such as up-selling opportunities can be clearly scoped and delivered. We call the results Customer Value Indexes (CVIs) for brands, vendors, assets and financing.
Want to learn more about Cerebri AI? Visit Cerebri AI's website.
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