Data Analyst / Data Scientist

Job Description

Gather, clean, and validate data from various sources (databases, APIs, and third-party tools). Maintain and improve data accuracy and integrity. Ensure that data flows smoothly from source to destination so that it can be processed Utilize strong database skills to work with large, complex data sets to extract insights Filter and cleanse unstructured (or ambiguous) data into usable data sets that can be analyzed to extract insights and improve business processes Identify new internal and external data sources to support analytics initiatives and work with appropriate partners to absorb the data into new or existing data infrastructure Build tools for automating repetitive asks so that bandwidth can be freed for analytics Collaborate with program managers and business analysts to help them come up with actionable, high-impact insights across product lines and functions Work closely with top management to prioritize information and analytic needs Create dashboards and reports using visualization tools (e.g., Power BI). Conduct statistical analyses (e.g., regression, hypothesis testing) to support predictive and descriptive insights. Assist in building data models to enhance forecasting capabilities. Requirements: Bachelors or Masters in a quantitative field (such as Engineering, Statistics, Math, Economics, or Computer Science with Modeling/Data Science), preferably with work experience of over 3 years. Proficiency in SQL for querying and database management. Strong skills in Python, R, or Excel for data analysis and modeling. Proven problem solving and debugging skills. Familiar with database technologies and tools (SQL/R/SAS/JMP etc.), data warehousing, transformation and processing. Work experience with real data for customer insights, business and market analysis will be advantageous. Experience with text analytics, data mining and social media analytics. Statistical knowledge in standard techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks, Random Forests, Ensembles, etc. Excellent communication and presentation skills is a MUST