Data Scientist

You are a research scientist and engineer who wants to work in the areas of machine learning, natural language processing, information extraction, graphical models, summarization, information retrieval, recommend systems, and/or knowledge graphs. You will bring new ideas, evangelizing them, and shepherding their adoption within the team. You extract and identify relevant, meaningful, and actionable information from structured and unstructured data in real-time and provide advanced ways of accessing this data (such as search, summarization, and recommendations).

What you will do:

• Write code (Python, R, SQL, Java, etc.) to obtain, clean, manipulate, and analyze data.
• Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
• Analyze historical data to identify trends and support optimal decision making.
• Build machine learning and statistical models to solve specific business problems.
• Leverage AI/LLM frameworks to develop internal and external solutions.
• Identify opportunities for improving workflows to increase data quality, accuracy, and timeliness.
• Design experiments to test hypotheses and measure the effectiveness of solutions.
• Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Determine why such examples are outliers and if action is needed.
• Work across teams to deliver enhancements, features, and time-sensitive projects.
• Deliver reports or presentations to share insights to audiences of varying levels of technical sophistication.

You need to have:

• Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• 5-7 years of experience working with large projects and diverse data sets, including preprocessing, cleansing, and verifying the integrity of data.
• Proficiency in Python and SQL, R, or Java, and experience with data analysis libraries (pandas, NumPy, scikit-learn).
• Experience with data visualization tools (Tableau, Power BI, QuickSight, matplotlib, seaborn).
• Experience with Database Management Systems (Oracle, PostgreSQL, MySQL, Redshift, etc.).
• Experience with distributed computational frameworks (YARN, Spark, Hadoop, Kubernetes, Docker), cloud-based computing (Apache Solr, Lucene, or Elasticsearch).
• Knowledge of descriptive and inferential statistics, regression, supervised and unsupervised learning methods, multivariate and univariate hypothesis testing.
• Strong problem-solving and analytical skills.
• Excellent communication skills and willingness to learn from senior team members.
• Effective project management skills and ability to prioritize tasks.
• Ability to work quickly, accurately, and efficiently in a fast-paced environment with shifting priorities.

Equal Opportunity

Bloomberg Industry Group maintains a continuing policy of non-discrimination in employment. It is Bloomberg Industry Group’s policy to provide equal opportunity and access for all persons, and the Company is committed to attracting, retaining, developing, and promoting the most qualified individuals without regard to age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law (“Protected Characteristic”). Bloomberg prohibits treating applicants or employees less favorably in connection with the terms and conditions of employment, in all phases of the employment process, because of one or more Protected Characteristics (“Discrimination”).