A Data Analyst develops computer programs to analyze large customer information databases for companies and organizations. Analyzes data to identify patterns and provide information relevant to a particular business, industry or field; analysis may be used for marketing, or to detect fraud in financial transactions, or for research. Develops computer programs to protect confidential customer information.
Data Analysis & SQL — Strong EDA skills with advanced SQL proficiency Setting Goals & Success Metrics — Ability to collaborate with stakeholders on defining OKRs and measuring progress 10+ years of quantitative/analytical experience — Using scripting languages (Python), statistical tools, and data querying at scale
Nice-to-Have Skills:
Visualization — Designing dashboards and high-performance reports Storytelling Through Data — Communicating insights to technical and non-technical audiences Predictive/Forecasting Modeling — Regression, clustering, classification techniques
Minimum Years of Experience:
10+
Years Description:
We are seeking a highly skilled Data Scientist with 10+ years of industry experience to join our team. The successful candidate will have a strong background in data analysis, statistical modeling, and data visualization, as well as excellent communication skills.
Key Responsibilities:
Data Analysis:
Perform exploratory data analysis (EDA) to identify trends, patterns, and correlations; apply statistical and quantitative tools or techniques; interpret data and formulate deep-level insights.
Setting Goals and Success Metrics:
Collaborate with stakeholders to define business objectives and key results (OKRs); define success metrics that measure short and long-term progress towards OKRs.
Visualization:
Design visualizations that provide a clear narrative understanding as well as deep dive capabilities; develop high-performance reports and dashboards.
Storytelling Through Data:
Develop compelling narratives to communicate data insights for technical and non-technical audiences; utilize various relevant tools and techniques to effectively present data; provide recommendations based on analytical findings and insights, with prioritization of actions and estimated impact.
Modeling:
Develop and implement predictive and forecasting models using multiple techniques such as regression, clustering, classification, and more; evaluate and refine models based on performance metrics; generate actionable insights from model output.
Research and Experiment:
Formulate multiple hypotheses that are tied together to answer business questions; develop a comprehensive research plan that identifies appropriate data collection tools, techniques, or methods to be used for a specific research problem; conduct research with appropriate methods to answer the research questions or test hypotheses.
Requirements:
10+ years of industry experience solving analytical problems using quantitative approaches, including defining metrics and goals, monitoring key metrics, understanding root causes of changes in metrics, and exploratory analysis to Client new opportunities. 10+ years of industry experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R). Strong background in data analysis, statistical modeling, and data visualization. Excellent communication skills, with the ability to present complex data insights to both technical and non-technical audiences. How many rounds of interviews? 2 - 3 rounds
