Назад
4 дня назад

Data Scientist

Формат работы
remote (только India)
Тип работы
fulltime
Грейд
junior
Страна
India
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Описание вакансии

Data Scientist

Conditions

Posted Date Mar 21, 2026 Employment Type Full-time Experience Level Entry level Location India Category ** Data Science ** Company **iConsultera **

Data Scientist

Role Overview We are looking for a Data Scientist to analyze large datasets, build predictive models, and generate actionable insights to support business decisions. You’ll work with cross-functional teams to turn data into meaningful solutions in a fully remote setup.

Key Responsibilities

  • Collect, clean, and analyze structured and unstructured data
  • Build and deploy machine learning models
  • Perform data exploration and statistical analysis
  • Develop dashboards, reports, and data visualizations
  • Collaborate with product, engineering, and business teams
  • Communicate insights and recommendations to stakeholders Interested in remote work opportunities in Data Science? Discover Data Science Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
  • Optimize model performance and accuracy
  • Work with large datasets using scalable tools and techniques

Required Skills

  • Strong programming skills in Python or R
  • Experience with data analysis libraries (Pandas, NumPy, Scikit-learn)
  • Knowledge of machine learning algorithms
  • Strong understanding of statistics and probability Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
  • Experience with SQL and databases
  • Data visualization skills (Power BI, Tableau, Matplotlib, Seaborn)
  • Problem-solving and analytical thinking

Preferred Skills

  • Experience with deep learning frameworks (TensorFlow, PyTorch)
  • Knowledge of big data tools (Spark, Hadoop)
  • Familiarity with cloud platforms (AWS, Azure, GCP)
  • Experience in NLP, computer vision, or recommendation systems
  • Understanding of MLOps and model deployment

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