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Data Scientist

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Overview:

The Data Scientist plays a crucial role in leveraging data to drive business insights develop datadriven strategies and enhance decisionmaking processes. They are responsible for applying advanced analytics and machine learning techniques to interpret complex data sets identify trends and forecast future outcomes.

Key Responsibilities:

  • Develop and implement machine learning models for predictive and prescriptive analysis.
  • Collect clean and preprocess data for analysis and modeling purposes.
  • Conduct exploratory data analysis to discover trends and patterns in data.
  • Create and maintain data pipelines and infrastructures for efficient data retrieval and storage.
  • Collaborate with crossfunctional teams to identify business needs and opportunities for leveraging data to drive business solutions.
  • Design and execute A/B tests to evaluate the effectiveness of different strategies and solutions.
  • Develop and deploy datadriven solutions and algorithms to address business challenges.
  • Present findings and insights to stakeholders using data visualization techniques.
  • Stay updated with the latest advancements in data science and machine learning technologies.
  • Contribute to the development and implementation of data governance and data quality standards.
  • Conduct adhoc analysis and provide datadriven insights to support strategic decisionmaking.
  • Collaborate with data engineers to optimize data infrastructure and improve data accessibility.
  • Lead and mentor junior data analysts and data scientists.
  • Participate in the design and development of data science projects and initiatives.
  • Contribute to the creation and maintenance of best practices in data science and analytics.

Required Qualifications:

  • Bachelors or Masters degree in Computer Science Statistics Mathematics or related field.
  • Proven experience in developing and deploying machine learning models and algorithms.
  • Proficiency in programming languages such as Python R or Java.
  • Solid understanding of statistical analysis hypothesis testing and experimental design.
  • Experience with big data technologies and platforms such as Hadoop Spark or MapReduce.
  • Expertise in data visualization tools and techniques (e.g. Tableau Power BI Matplotlib).
  • Demonstrated knowledge of database management and query languages including SQL and NoSQL databases.
  • Strong communication and presentation skills with the ability to convey complex findings to nontechnical stakeholders.
  • Experience in designing and implementing data pipelines and ETL processes.
  • Ability to work in a fastpaced collaborative environment and manage multiple projects simultaneously.
  • Solid understanding of cloud computing platforms such as AWS Azure or Google Cloud.
  • Knowledge of advanced analytics including time series analysis clustering and classification techniques.
  • Experience with data mining feature engineering and data preprocessing techniques.
  • Strong problemsolving skills and the ability to think critically and analytically.
  • Proven track record of delivering actionable insights and recommendations based on data analysis.

machine learning,python,data analysis,statistics,sql,data visualization,big data,predictive modeling

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