Data Scientist
New York City, United States
Full Time Mid-level / Intermediate USD 135K - 155K
New York University
Position Summary
The Data Scientist will work on collecting, analyzing, processing, and presenting large sets of data to inform decision-making. Apply technical, analytical, and programming skills to extract, clean, and analyze external and internal data using statistical methods and machine learning algorithms to build predictive models to uncover meaningful patterns in the data. Leverage a broad set of technologies to evaluate the performance of models using various metrics and techniques to ensure their accuracy and generalization to deliver transformational insights from data. In collaboration with stakeholders, develop innovative strategies for data-derived insights by working with various schools and units to design and implement data analysis strategies to solve business problems through fact-based and scientific analytics. The ideal candidate will possess strong proficiency in data science tools and techniques and will thrive in an independent work environment, taking initiative and ownership of projects from start to finish.Qualifications
Required Education:Master's Degree or equivalent Preferred Education:Master's Degree in a Quantitative degree (Engineering, Mathematics, Statistics, Computer Science or computation-intensive Sciences and Humanities). Required Experience:5+ years experience translating business problems into data problems with different stakeholders or an equivalent combination of education and experience. Relevant training/experience in data science and/or statistical methods. Preferred Experience:2+ years experience in quantitative and qualitative research, statistical analysis, reporting, and/or data analysis of large, longitudinal data sets. Familiarity with the operational and business needs of a large higher education institution. Required Skills, Knowledge and Abilities:Demonstrated experience querying and processing large data sets. Demonstrated experience in statistical approaches to build predictive models (time series, clustering, neural networks) Demonstrated ability to tell stories with data using data visualization software or other reporting/BI tools (such as Tableau, PowerBI, ArcGIS, etc.). Demonstrated experience in programming/scripting languages and statistical software (such as R, Python, NumPy, pandas, scikit-learn, or PySpark). Demonstrated testing approaches for statistical and machine-learning analysis methods, software, and data sources for continual improvement of quantitative solutions. Demonstrated experience working with different file formats: CSV, JSON, Avro, Parquet etc., and data compression techniques Demonstrated strong verbal and interpersonal communication skills. Demonstrated proficiency in written communication skills. Demonstrated ability to communicate advanced analytical concepts and complex quantitative analysis in a concise, clear, and actionable manner. Demonstrated ability to respond to changing priorities and ensure timely, accurate deliverables. Demonstrated ability to work with diverse groups/populations. Familiarity working with cloud platforms & services (AWS, GCP or Azure)Additional Information
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is USD $135,000.00 to USD $155,000.00. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses, clinical compensation, or other items. NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/nyugreen.EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender IdentityTags: Avro AWS Azure Clustering Computer Science CSV Data analysis Data visualization Engineering GCP JSON Machine Learning Mathematics NumPy Pandas Parquet Power BI PySpark Python R Research Scikit-learn Statistics Tableau Testing
Perks/benefits: Equity Startup environment Transparency
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