Principal Data Scientist
Found in: Resume Library US A2 - 1 week ago
As a Principal Data Scientist, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.
Key Responsibilities
Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
Advocate and educate on the value of data-driven decision making; focus on the “how and why” of solutioning.
Lead analytic approaches; integrate solutions collaboratively into applications and tools with data engineers, business leads, analysts and developers.
Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products.
Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources.
Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
Collaborate, coach, and learn with a growing team of experienced Data Scientists.
Stay connected with external sources of ideas through conferences and community engagements
Requirements
Bachelors Degree in Data Science, Computer Science, or related field
10+ years of Data Science and Machine Learning experience required
Proficiency in Python or R. Ability to write complex SQL queries
Proficiency with Machine Learning concepts and modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets.
Ability to implement ML best practices for the entire Data Science lifecycle
Ability to apply various analytical models to business use cases (NLP, Supervised, Un-Supervised, Neural Nets, etc.)
Experience with Azure AI Document Intelligence is must have.
Exceptional communication and collaboration skills to understand business partner needs and deliver solutions
Bias for action, with the ability to deliver outstanding results through task prioritization and time management
Experience with data visualization tools — Tableau, Power BI, etc. preferred
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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