Conducting research leveraging big data technologies that surface actionable insight that influence analytical solutions roadmap; Gathering and processing raw data at scale by using statistical packages like R, and programming language like Python, Java, Scala; Processing unstructured data into a form suitable for analysis and then do the analysis; Utilizing Image processing and Computer Vision; Assessing how AI capabilities can best be applied to complex business situations; Creating and implementing machine learning algorithms and advanced statistics, and employing statistical computing languages for data analysis; Working closely with engineering team to integrate your ideas, innovations and algorithms into production systems; Analyzing large, complex multi-dimensional datasets using a variety of tools and statistical environments; Supporting business decisions with ad hoc analysis as needed; Querying databases with structured and un-structured data and performing statistical analysis; and Building deep learning models in production for predicting ideal vendor capacity, order volume. Job Requirements: Masters Degree in Computer Science, or a related engineering or technical field and experience, training or coursework performing Exploratory Data Analysis, Data Visualization, Feature Engineering, Statistical analysis, Hypothesis Testing, A/B Testing, Class Imbalance Handling, Hyperparameter Tuning, and using Python, SQL, Machine learning algorithms, Regression Models, Support Vector Machines (SVM), Random Forest Model, XGBoost Model, clustering, Principal Component Analysis (PCA), Neural Networks, RNN, BERT, BART, Natural Language Processing (NLP), Keras, Pandas, NumPy, Scikit, Hugging Face Model, Deep Learning, LLMs, Transformers, Computer Vision, Vision Transformers, TensorFlow, and PyTorch. Company headquarters is located in Moon Township, PA, but telecommuting is permitted from anywhere in the United States. Qualified applicants may apply for this position with ServiceLink Services, LLC by sending resumes to (email removed).
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