Description
feature engineering
model development
analytics integration
client engagement
team coaching
ai architecture
Key interfaces: Offering owners and SMEs across industry verticals, Solution architects, delivery head, digital sales team, account sales team, account delivery team
A Data Scientist applies strong expertise in artificial intelligence through use of machine learning, data mining, and information retrieval to design, prototype and build next generation advanced analytics engines and services. The data scientist collaborates with business partners to define the technical problem statement and hypothesis to test; develops efficient and accurate analytical models that mimic business decisions and incorporates them into analytical data products or tools with the support of a cross-functional team.
Role summary: Join the founding team and scale Cyient’s technical CoE for AI/ML with responsibilities across architecting solutions for deal pursuit and client engagements, PoC development, delivery of client engagements, focused IP/ accelerator development
- Collaborate, coach, and learn with a growing team of experienced Data Scientists
- Lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts and developers
- Stay connected with external sources of ideas through conferences and community engagements
- Advocate and educate on the value of data driven decision making focusing on the “how and why” of solving problems
- Share their passion for Data Science with broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards
- Effectively communicate the analytics approach and how it will meet and address objectives to business partners
- Collaborate with business partners to develop novel ways to meet objectives utilizing cutting edge techniquesand tools
- Engineer features by using their business acumen to find new ways to combine disparate internal and external data sources
- Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products
Requirements
sql
python
machine learning
spark
tableau
phd
Digital Experience/Individual Skills
- Number sense; healthy skepticism around validity of data and its inherent biases
- Exemplary organizational skills with attention to detail & accuracy
- Bias for action, with ability to deliver outstanding results through task prioritization and time management
- Bachelor’s in Data Science, Computer Science, Engineering, Statistics and 5+ years experience required OR Graduate degree in quantitative discipline and demonstrated Data Science skill set, plus 2+ years work experience
- Must have proficiency writing complex SQL queries
- Ability to coach, mentor, and collaborate with business partners, analysts, and team members
- Intellectual curiosity to understand and answer questions
- Bachelor’s degree required, MS or PhD preferred
- Exceptional communication and collaboration skills to understand business partner needs and deliver solutions
- Must have Python proficiency working with DataFrames
- Must have proven ability to merge and transform disparate internal & external data sets together to create new features
- Must have proficiency with Machine Learning to solve clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets
- Demonstrated ability to efficiently learn and solve new business domains and problems
- Intellectual humility to leverage the expertise of others
- Experience with Big Data technologies desired — Spark, Cloud AI platforms, containerization
- Experience with data visualization tools preferred — Tableau, Plotly, etc.
- Experience with supporting deployment, monitoring, maintenance and enhancement ofmodels desired
Benefits
Information not given or found
Training + Development
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