Analytics Data Science And Iot Lead Job in Hexaware Technologies Ltd
Analytics Data Science And Iot Lead
Hexaware Technologies Ltd
4+ weeks ago
- Mumbai, Maharashtra
- Not Disclosed
- Full-time
- Permanent
Job Summary
The Role offers Opportunity to join a global team to do meaningful work that contributes to global strategy and individual development To re-imagine, redesign, and apply technology to add value to the business and operations Multiple opportunity to showcase candidates strong analytical skills and problem-solving ability Ways to grow as an individual and expand the domain knowledge to be able to add value
Essential Skills Provide expert advice on identifying patterns in data. This includes having a keen sense of pattern detection and anomaly detection. Machine learning & Deep Learning: Hands on experience Experience with Natural Language Processing techniques Hands-on experience with SQL Hands on in statistical software packages (e.g., R, Python, SAS or SPSS) At least one cloud platform experience ( E.g. Azure , AWS or GCP ) Exposure to Natural Language Generation Data storytelling: Communicate actionable insights using data, often for a non-technical audience. Business intuition: Connect with stakeholders to gain a full understanding of the problem at hand Interpersonal skills: Communicate across a diverse audience across all levels of an organization.
Essential Qualification BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Statistics or another quantitative field is preferred Preferred PHD in Data science/Statistics
HIR ING
Job Skills
Data Science - Python, Data Science - Python, BI/BA
Description
Responsibilities Understanding the overall Business Strategies, vision, plans and specific requirement to align with Data Science efforts Agree with the customer on the Acceptance Criteria and communicate to the team Making sure the team understands the Business Processes and data Manage EDA (Exploratory Data Analysis), Data Sourcing/Cleansing, Data preprocessing data munging and create training data sets Ensuring appropriate and correct modelling techniques are used Guide the team in deployment of the statistical model using the technology of customers preference Making sure the Data Pipeline, Machine Learning Pipeline and Monitoring activities are set for Continuous Integration , Continuous Development and Continuous Testing Act as the go-to-person for all the issues in Machine Learning Life Cycle Partners with IT and business teams to effectively operationalize models Ensure continuous monitoring through the system and advise on fine-tune/re-build the modelsThe Role offers Opportunity to join a global team to do meaningful work that contributes to global strategy and individual development To re-imagine, redesign, and apply technology to add value to the business and operations Multiple opportunity to showcase candidates strong analytical skills and problem-solving ability Ways to grow as an individual and expand the domain knowledge to be able to add value
Essential Skills Provide expert advice on identifying patterns in data. This includes having a keen sense of pattern detection and anomaly detection. Machine learning & Deep Learning: Hands on experience Experience with Natural Language Processing techniques Hands-on experience with SQL Hands on in statistical software packages (e.g., R, Python, SAS or SPSS) At least one cloud platform experience ( E.g. Azure , AWS or GCP ) Exposure to Natural Language Generation Data storytelling: Communicate actionable insights using data, often for a non-technical audience. Business intuition: Connect with stakeholders to gain a full understanding of the problem at hand Interpersonal skills: Communicate across a diverse audience across all levels of an organization.
JD:
Python developer (Data science) who is well-versed in NLP techniques and libraries such as spaCy and Machine learning concepts. - Grade: G4/G5, Relevant work experience in NLP techniques and ML concepts: Min 2 years.
Essential Qualification BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Statistics or another quantitative field is preferred Preferred PHD in Data science/Statistics
Experience Required :
6 to 9 Years
Vacancy :
2 - 4 Hires
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