Job DescriptionSr. ML Data Scientist
As Sr. ML Data Scientist, you will apply strong expertise in Artificial Intelligence through the use of ML, data mining, & data retrieval to design, prototype, & build next generation advanced analytics engines & services. You’ll collaborate with cross-functional teams & business partners to define the tech problem statement & hypotheses to test. You will develop efficient & accurate analytical models which mimic business decisions & incorporate those models into analytical data products & tools. You will have the opportunity to drive current & future strategy by leveraging your analytical skills as you ensure business value & communicate the results.
Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques & tools.
Effectively communicate the analytics approach & how it will meet & address objectives to business partners.
Advocate & educate on the value of data-driven decision making; focus on the “how & why” of solutioning.
Lead analytic approaches; integrate solutions collaboratively into applications & tools with data engineers, business leads, analysts & developers.
Create repeatable, interpretable, dynamic & 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 & external data sources.
Share your passion for Data Science with the broader enterprise community; identify & develop long-term processes, frameworks, tools, methods & standards.
Collaborate, coach, & learn with a growing team of experienced Data Scientists.
Stay connected with external sources of ideas through conferences & community engagements
Min BS Degree in Data Science, Computer Science, or related field
2-5 years of Data Science & ML experience required
Proficiency in Python or R. Ability to write complex SQL queries
Proficiency with ML concepts & modeling techniques to solve problems such as clustering, classification, regression, anomaly detection, simulation & 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.)
Exceptional communication & collaboration skills to understand business partner needs & deliver solutions
Bias for action, with the ability to deliver outstanding results through task prioritization & time management
Experience with data visualization tools — Tableau, R Shiny, etc. preferred