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Data Science Lead - R01570348

📅 Sep 7
PythonStatistical ModelingMachine LearningFeature Engineering
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📜 Description

  • Translate business challenges into structured data science problems aligned with measurable outcomes.
  • Develop, monitor, and validate OKRs using statistical techniques.
  • Wrangle, cleanse, and transform large datasets for modeling and analysis.
  • Communicate data-driven insights through storytelling and visualization.
  • Guide modeling decisions, improve model performance, and balance efficiency with business needs.
  • Partner with engineering and product teams to implement scalable solutions and promote data literacy.

🛠️ Requirements

  • Translate complex business challenges into structured data science problems, ensuring alignment with organizational objectives and measurable outcomes
  • Develop, monitor, and validate OKRs using advanced statistical techniques to deliver actionable insights and track progress
  • Execute advanced data wrangling, cleansing, and transformation on large, complex datasets to enable robust modeling and analysis
  • Deliver impactful data-driven insights through clear data storytelling, utilizing visualization tools to communicate findings effectively to stakeholders
  • Apply design thinking methodologies to create innovative analytical solutions and continuously optimize data science workflows and processes
  • Lead technical decision-making for modeling iterations, optimizing model performance, and balancing computational efficiency with business requirements
  • Collaborate with cross-functional teams, including engineering and product, to implement scalable data science solutions that drive business value
  • Promote data literacy and foster a culture of data-driven decision-making by sharing best practices and industry trends across the organization
  • Advanced proficiency in Python or R for data wrangling, preprocessing, and statistical analysis
  • Expertise in statistical modeling and validation of performance metrics
Full job description
Senior Data Scientist

Job requirements

Experience Range: 5 - 8 years of experience, including at least 5 years of hands-on work in data science, analytics, or related fields, with recent exposure to agentic AI solutions Key Responsibilities:
  • Translate complex business challenges into structured data science problems, ensuring alignment with organizational objectives and measurable outcomes
  • Develop, monitor, and validate OKRs using advanced statistical techniques to deliver actionable insights and track progress
  • Execute advanced data wrangling, cleansing, and transformation on large, complex datasets to enable robust modeling and analysis
  • Deliver impactful data-driven insights through clear data storytelling, utilizing visualization tools to communicate findings effectively to stakeholders
  • Apply design thinking methodologies to create innovative analytical solutions and continuously optimize data science workflows and processes
  • Lead technical decision-making for modeling iterations, optimizing model performance, and balancing computational efficiency with business requirements
  • Collaborate with cross-functional teams, including engineering and product, to implement scalable data science solutions that drive business value
  • Promote data literacy and foster a culture of data-driven decision-making by sharing best practices and industry trends across the organization
  • Required Skills:
  • Advanced proficiency in Python or R for data wrangling, preprocessing, and statistical analysis
  • Expertise in statistical modeling and validation of performance metrics
  • Experience with data visualization tools such as Tableau, Power BI, or Matplotlib
  • Hands-on experience with machine learning algorithms and evaluation metrics
  • Strong background in feature engineering and data mining
  • Familiarity with big data technologies such as Spark or Hadoop
  • Experience with cloud-based data platforms including AWS, Azure, or Google Cloud
  • Knowledge of MLOps practices and deployment pipelines
  • Preferred Skills:
  • Experience with deep learning frameworks such as TensorFlow or PyTorch
  • Exposure to agentic AI and rapid domain adaptation
  • Experience with automation tools and scripting for data workflows
  • Desired Qualifications:
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
  • Certification in Data Science or Machine Learning from a recognized institution, such as Microsoft Certified: Azure Data Scientist Associate or IBM Data Science Professional Certificate
  • Relevant coursework or certification in statistical analysis or business analytics
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