Remote - Data Scientist (Python, NLP, Statistics, ML)

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Posted 11 days ago United States Salary undisclosed
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Job Description

Title: Data Scientist (Python, NLP, Statistics, ML) Roles & Responsibilities Apply statistics, mathematics, data science, machine learning techniques and solutions meet software requirements. Design and implement machine learning architecture and methods per clients requirement. Enhance and maintain current analysis tools, including automation of current processes using AI/ML algorithms. Build supervised and un-supervised models for risk prediction, anomaly detection and timeseries analysis. Conduct quantitative data analysis using a variety of large structured and unstructured datasets, including developing retrieval, processing, fusion, analysis, and visualization of various datasets. Identify and test hypotheses, ensuring statistical significance, as part of building predictive models for business application. Translate quantitative analysis, findings into accessible visuals for non-technical audiences, and provide a clear view into data interpretation. Enable business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes. Maintain understanding of strategic goals, business challenges and customer needs. Write clean scripts for data analysis, ETL, and visualization. Prepare and present findings of investigations & solutions to stakeholder. Help your team understand use of various analytics/statical/ machine learning tools and methods. Bring your curiosity, innovative spirit, and passion to deliver on the promise of technology in a difficult, competitive, and exciting vertical. Required Qualifications & Experience: Masters degree or higher in Computer Science, Data Science, Engineering, Mathematics, Applied Statistics, or related field. Experience 3+ years with machine learning in industry environment. Experience 5+ years coding in Python, Scala, or similar. Advanced understanding of probability, statistics, machine learning, data science. Expertise in data correlation/feature analysis, analysis of machine learning models, and optimizing models for accuracy. Proficiency in transforming and cleaning data & working across multiple models. Ability to research and manipulate complex and large data sets (both distributed and non-distributed Strong fundamentals in problem solving, algorithm design, and model building. Ability to solve complex business problem through logical and creative thinking. Strong ability to synthesize complex information. Excellent Code writing capability in Python and familiarity with relevant ML packages. Familiarity with libraries such as Pandas, Scikit-learn etc. Experience of working on Fraud detection solution. Excellent knowledge of anomalies/outliers detection using unsupervised algorithms clustering, Local Outlier Factor, Isolation Forest , etc. Deep learning experience would be added advantage. Experience with Spark DataBricks frameworks. Interest in applying data science in the fields of compliance. Strong written and verbal communication skills.