Sr Data Scientist

Posted 3 days agoViewed

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💎 Seniority level: Senior, 3 years

📍 Location: United States

💸 Salary: 211536.0 - 287100.0 USD per year

🔍 Industry: Software Development

🏢 Company: jobs

🗣️ Languages: English

⏳ Experience: 3 years

🪄 Skills: PythonSQLCloud ComputingData AnalysisETLGitMachine LearningNumpyTableauAlgorithmsData engineeringData StructuresPandasSparkTensorflowAgile methodologiesData visualizationData modeling

Requirements:

SQL and Python programming to query and validate the accuracy of datasets
Design and develop workflow orchestration tools
Python scripting to develop statistical and machine learning models for classification
Use agile software development principle to design, plan and structure deployment of software products
Develop machine learning models to segment customer behavior, identify market concentration and volatility using Python and Spark ML
Building KPIs (Key Performance Indicators) and metrics, validating using statistical hypothesis testing
Expertise in Cloud Computing resources and maintaining data on cloud storage
Big Data processing for data cleaning
Deploy self-serving data visualization tools, automating, generating reports and consolidating visually on tableau dashboards
Develop data engineering pipelines and transformations

Responsibilities:

Lead, build and implement analytics functions for Honey features
Conduct impactful data analysis to improve customer experiences and inform product development
Collaborate cross-functional support teams to build world-class products and design hypothesis-driven experiments
Gather and collate business performance and metrics to recommend improvements, automation, and data science directives for overall business performance
Present findings and recommendations to senior level/non-technical stakeholders
Maintain large datasets by performing batch scheduling and pipelining ETL operations
Perform ad-hoc exploratory analysis on datasets to generate insights and automate production ready solutions
Develop machine learning-based models to improve forecasting and predictive analytics
Implement innovative quantitative analyses, test new data wrangling techniques, and experiment with new visualization tools to deliver scalable analytics
Develop and create programming paradigms and utilizing tools like git, data structures, OOP, and network algorithms

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