Data Scientist

Responsibilites

  • Employing robust statistical and machine learning methods to analyze large datasets of IoT data.
  • Designing and implementing machine learning models, and fine-tuning existing ones.
  • Leveraging classical machine learning methodologies including but not limited to decision trees, logistic regression, SVM, and clustering.
  • Transforming raw data into meaningful insights that drive strategic decision-making.
  • Implementing rigorous testing methodologies to ensure the validity and reliability of data analyses.
  • Effectively communicating findings, insights, and proposed solutions to non-technical stakeholders.
  • Developing and maintaining documentation regarding procedures, methodologies, and interpretations.
  • Staying updated with emerging trends and advancements in data science and machine learning.

Requirements

  • A Bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Data Science, or a related field. Equivalent experience may be considered.
  • At least 3 years of experience in a data science role.
  • Proficient in Python or R and associated data science libraries (like Pandas, Numpy, Scikit-learn, Prophet, Pytorch).
  • Deep understanding and experience with classical machine learning algorithms including but not limited to regression models, decision trees, SVM, ensemble methods, and clustering.
  • Proven experience in ensuring model output explainability, and the ability to effectively communicate model workings and outputs to technical and non-technical stakeholders.
  • Excellent problem-solving skills, attention to detail, and critical thinking abilities.
  • Comfortable working both independently and collaboratively within a team.

Advantages

  • Experience with databases (SQL and NoSQL) and handling large datasets.
  • Familiarity with big data frameworks (like Hadoop or Spark) is a plus.
  • Understanding of data structures and algorithms, and their application in data-intensive computations.

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