• Us Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 20th Aug 2021

·         Be familiar with different machine learning or deep learning algorithms.

·        Experimental design and data acquisition experience.

·        Develop and demonstrate data analytics algorithms.

·        Develop and evaluate models in Matlab/Dymola/Python environment.

·        Assess the adequacy of the models for control, analytics and optimization purpose.

·        Guide the team with technical rationale on what model fidelity is needed and, on the need, to choose advanced control logics and strategies.

·        Evaluate and analyze related lab and field data.

·        Conduct system/dynamic analysis of customer products.

·        Demonstrated ability to work independently and in a team environment.

·        Basic understanding of thermal fluid systems, and thermodynamic cycles.

·        Knowledge of machine learning, linear algebra, statistics, and optimization is a plus.

·        Hand-on experience with embedded system and lab testing is also a plus.

·        Strong technical abilities to provide high quality documentation and standard work.

·        Prior experience with first principle or data driven or hybrid models and benchmarking with real time or experimental/lab data.

·        Development of detection algorithms suitable for use with low cost embedded platforms.

·        Experience in advanced analytical skills on data analytics or big data.

·        Data analytics algorithm development based on machine learning or physics model.

·        Proficient in data visualization tools such as Tableau, Python Matplotlib, R Shiny to create visually powerful and actionable interactive reports and dashboards.

·        Experience in Agile methodology and SCRUM process.

 

·         Databases: MySQL, Postgre SQL, Oracle, HBase, Amazon Redshift, MS SQL Server, Teradata.

·         Statistical Methods: Hypothetical Testing, ANOVA, Time Series, Confidence Intervals, Bayes Law, Dimensionality Reduction, Cross-Validation, Auto-correlation.

·         Machine Learning: Regression analysis, Bayesian Method, Decision Tree, Random Forests, Support Vector Machine, Neural Network, Sentiment Analysis, Linear Regression, Logistic Regression, Random Forest, PCA, SVM, Clustering, ARIMA/Time Series Analysis, Sentiment Analysis/Text Mining.

·         Libraries: Pandas, NumPy, Scikit-Learn, Jupyter Notebook

·         Hadoop Ecosystem: Hadoop 2.x, Spark 2.x, MapReduce, Hive, HDFS, Sqoop, Flume

·         Data Visualization: Tableau, MatPlotLib, Seaborn, ggplot2

·         Languages: Python (2.x/3.x), R, SAS, SQL, T-SQL, Matlab, Simulink, Scala, SQL, C/C++, Java, Modelica, MongoDB, Django, Flask

·         Operating Systems: PowerShell, UNIX/UNIX Shell Scripting, Linux and Windows

·         Collaborate with product design and engineering to develop an understanding of needs.

·        Research and devise innovative statistical models for data analysis.

·        Communicate findings to all stakeholders.

·        Enable smarter business processes and implement analytics for meaningful insights.

·        Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products.

·        Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.

·        Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.

·        Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.

·        Analyze data for trends and patterns and Interpret data with a clear objective in mind.

·        Implement analytical models into production by collaborating with software developers and machine learning engineers.

·        Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems.

·        Develop test plans for sensor systems in partnership with stakeholders

·        Develop project timelines and progress reports

·        Collaborate with business units and universities, and external providers

·        Lead and write standard work for evaluation, testing, and qualifications of and sensors systems and control electronics

·        Work within a project team environment, organize and lead task teams and help mentor team members

·        Keep current with technical and industry developments