Senior Manufacturing Data Scientist
Há 4 dias
Estimate Salary: $120,000 - $180,000 per year.
Job Description:We are seeking a highly skilled Senior Manufacturing Data Scientist to join our team at Tata Consultancy Services. As a key member of our data science team, you will be responsible for extracting valuable insights from manufacturing system data sources and developing predictive models to drive business growth.
Key Responsibilities:- Data Mining: Extracting usable data from various manufacturing system data sources
- Machine Learning: Selecting features, creating and optimizing classifiers using machine learning tools
- Data Preprocessing: Carrying out the preprocessing of structured and unstructured data
- Data Collection: Enhancing data collection procedures to include all relevant information for developing analytic systems
- Data Validation: Identifying appropriate methodology / tools for processing, cleansing, and validating the integrity of data to be used for analysis
- Analytical Skills: Analyzing large amounts of information to find patterns and solutions
- Reviewing Data: Reviewing data & analytics work carried out by solution partner / suppliers
- Prediction Systems: Developing prediction systems and machine learning algorithms
- Presenting Results: Presenting results in a clear manner
- Solution Proposal: Propose solutions and strategies to tackle business challenges
Collaboration is key, so you'll work closely with Business and IT teams to ensure seamless integration and effective implementation of your findings.
Requirements:- 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
- Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc.
- 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
- Excellent Communication Skills with technical and non-technical audience
- Strong Software Engineering Background
- Problem-solving aptitude and analytical mind
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