Data & Analytics Scientist / Engineer

Required Technical Skill Set     Expertise in data & analytics of Manufacturing real time / transformed data, Factory Operational / Supply Chain KPIs

 Experience Range                      8+ year

Location of Requirement           Brazil

Desired Competencies (Technical/Behavioral Competency)

Must-Have

•          Bachelor’s degree in Engineering, Information Technology, Data Analytics, or a related field.

•             Expertise in Data Analytics of manufacturing real time data, factory operational / supply chain KPIs,  predictive / prescriptive analytics for manufacturing environment.

•             Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.

•             Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. and proficiency in statistics.

•             Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests etc.

•             Strong Math Skills - understanding the fundamentals of Multivariable Calculus and Linear Algebra and algorithm optimization techniques.

•             Data Wrangling – proficiency in handling imperfections in data.

•             Experience with Data Visualization Tools like PowerBI, matplotlib, ggplot, d3.js., or Tableau that help to visually encode data

•             Excellent Communication Skills with technical and non-technical audience

•             Hands-on experience with data science tools

Good-to-Have 

•             Strong Software Engineering Background

•             Problem-solving aptitude and analytical mind

Responsibility of / Expectations from the Role

1.           Data mining or extracting usable data from valuable manufacturing system data sources

2.           Using machine learning tools to select features, create and optimize classifiers

3.           Carrying out the preprocessing of structured and unstructured data

4.           Enhancing data collection procedures to include all relevant information for developing analytic systems

5.           Identifying appropriate methodology / tools for processing, cleansing, and validating the integrity of data to be used for analysis

6.           Analyzing large amounts of information to find patterns and solutions. Reviewing data & analytics work carried out by solution partner / suppliers

7.           Developing prediction systems and machine learning algorithms

8.           Presenting results in a clear manner

9.           Propose solutions and strategies to tackle business challenges

10.         Collaborate with Business and IT teams..

Important: 50% of the time to travel to Argentina, Travel to Argentina will be borne client

English Advanced mandatory