Data and Analytics Scientist

1 semana atrás

São Paulo, Brasil Tecnoalfa Tempo inteiro

Role: Smart Factory Data & Analytics Scientist / Engineer. We are looking for a Consultant with expertise in data & analytics of Manufacturing real time / transformed data, Factory Operational / Supply Chain KPIs.


Must-Have:

  • 8+ years of experience as a Data & Analytics Scientist in the manufacturing industry
  • 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:

  • Data mining or extracting usable data from valuable manufacturing system data sources
  • Using machine learning tools to select features, create and optimize classifiers
  • Carrying out the preprocessing of structured and unstructured data
  • Enhancing data collection procedures to include all relevant information for developing analytic systems
  • Identifying appropriate methodology / tools for processing, cleansing, and validating the integrity of data to be used for analysis
  • Analyzing large amounts of information to find patterns and solutions. Reviewing data & analytics work carried out by solution partner / suppliers
  • Developing prediction systems and machine learning algorithms
  • Presenting results in a clear manner
  • Propose solutions and strategies to tackle business challenges
  • Collaborate with Business and IT teams


Requirements:

  • Advance English

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