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Programming: Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala. Data Visualization: Visualization Tools: Libraries like Matplotlib, Seaborn (Python), ggplot2 (R), or tools like Tableau, PowerBI. Data Interpretation: Ability to interpret visualizations and convey findings.
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Display analytic results in text and visually using appropriate data science, business intelligence, and visualization tools, such as Python, R, SQL, Tableau, PowerPoint, Excel, and communicate results to client audiences at all levels with presentations and briefings.
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Data Wrangling Tools: Familiarity with tools and libraries like Pandas (for Python) or dplyr (for R). Big Data Technologies:Distributed Computing: Tools like Apache Spark, Hadoop.
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QualificationsTechnical: 3+ years in a hands-on role performing advanced predictive analytics using tools like Python, R, or Scala. Experience with applied machine learning (tree-based methods, ensemble methods, neural networks/deep learning)Proficient understanding of relational (e.g. Oracle, SQL Server, PostgreSQL) and Big Data distributed structures (Hadoop/Spark) in order to source data effectively.
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Experience in cloud environments with a blend of data science skills (remote sensing, physics, geospatial, imagery process, etc) and computer science understanding is a plus for this position.
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Leverage big data technologies to efficiently process and analyze very large datasets, similar to those encountered in a federal agency. Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis.
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Demonstrated experience working with large data sets, survey dataset experience is a plus. Working knowledge and experience using one of statistical computer languages (R, Python, SQL, Stata, etc.
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Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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Skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
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Working knowledge of statistical, query based, or data management software (e.g. SQL, SAS, R, Python, Tableau, Oracle OAC). Another Source’s client, Washington State University, is recruiting a Data and Strategy Analyst to join their team.
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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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Databases; and programming in one or more of the following: Python, R, Spark, Matlab, Stata, C, Perl, or Java; AND. databases; and programming in Python with experience in one of the following: R, Spark, Matlab, Stata, C, Perl, or Java; AND.
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Minimum qualifications: Bachelor’s degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience.
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Experience working with tools, including object-oriented programming (Python, Java), computational analysis tools (R, MATLAB), and associated data science libraries (scikit-learn.
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Basic electronics experience (e.g. fabrication, troubleshooting, schematic capture, PCB design) is a plus. Experience applying image processing, computer vision, and/or deep learning techniques to medical images is a plus.
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big data science a plus r python jobs Company: Endeavor in Alexandria, VA
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With the advent of desktop computers, the arduous task of scouring through weekly job classifieds became a thing of the past. The mid-1990s brought about a new era where job seekers could easily search and apply for jobs online. The introduction of AOL's Instant Messaging feature provided an even faster means for employers and candidates to communicate and schedule interviews. As smartphones became more pervasive in the early 2000s, hiring managers increasingly used phone calls for screening and interviewing candidates. Despite this trend, over 80% of interviews still took place in person.
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One day it's a covert statement to a mother returning to work after maternity leave. Another day it's a lingering gaze at an employee enjoying a culturally rich meal. These microaggressions (or sometimes macroaggressions) can take an employee from a confident, high-performer to one that feels insecure being themselves at work. Your employees engage with people with different ideas and feel most comfortable and valued when they can work without losing their cultural, racial, and gender identity. While most employers know this, why have workplace racism and sexism often been neglected?
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Building a Candidate Pipeline Through Internships
Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.