Data Scientist

1 week ago


Singapore RP International Ltd Full time

As a member of the Data Office Team, your role will involve utilizing both structured and unstructured data to address actual business challenges throughout the organization.

By doing so, you will contribute to increasing revenue, improving the customer experience, enhancing productivity, and mitigating risk.

RESPONSIBILITIES:

  • Collecting and cleaning data responsible for collecting data from various sources, cleaning and transforming it into a usable format for analysis.


Analyzing data
  • Using statistical and machine learning techniques, a data scientist analyzes data to identify patterns and trends. They use tools such as Python, R, SQL, and Tableau to analyze and visualize data.
  • Developing predictive models develops predictive models to forecast future trends or outcomes. They use statistical techniques such as regression analysis, decision trees, and neural networks to build these models.


Communicating insights
  • A data scientist communicates insights from data analysis to stakeholders in a clear and concise manner. They use data visualizations and other tools to communicate complex findings to a nontechnical audience.
  • Collaborating with crossfunctional teams
  • A data scientist works closely with crossfunctional teams such as product, engineering, and business to identify opportunities and solve complex problems.
  • Continuously improving models responsible for continuously improving predictive models to ensure accuracy and relevancy.
  • Staying up to date with industry trends and advancements in technology to identify new opportunities and stay ahead of the competition.

REQUIREMENTS:

  • 5 years+ of experience manipulating data sets and building statistical models, ideally with a Master's or PHD in Statistics, Mathematics, Computer Science or other quantitative field.
  • Strong programming experience, with solid understanding of software engineering design patterns and best practices.
  • Experience with big data technologies such as Hadoop, Impala and Hive.
  • Familiarity with SQLlike languages. No-SQL databases will be advantageous.
  • Knowledge of a variety of machine learning techniques. Able to design and implement complex statistical models and algorithms to extract insights from data, and effectively communicate those insights to stakeholders to drive business decisions.
  • Experienced in the use of CI/CD and DevOps tools

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