RRemotevilleRemote roles worth applying for.

How Remoteville checks and expires listings

Cognism logoCognism

Senior Data Scientist

Skills
Analytical SkillsAttention To DetailData ModelingData ScienceMachine LearningPredictive AnalyticsR
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • Master’s or higher preferred in Data Science, Computer Science, Mathematics, Statistics, Physics, or a related field
  • Expert proficiency in SQL, Python, and Spark
  • Strong experience in machine learning, AI, and big data technologies
  • Familiarity with AWS tools like S3, Iceberg, Glue Jobs, Athena, etc., is highly desirable
  • Experience with deep learning methodologies such as recurrent neural networks, transformers
  • Minimum 5 years of experience in a data science role with a demonstrated track record of delivering impactful data-driven solutions
  • Exceptional analytical skills with the ability to collect, organize, analyse, and disseminate significant amounts of information with attention to detail and accuracy
  • Excellent communication and interpersonal skills, with the ability to advocate for data-driven approaches to non-technical audiences.

Nice to have

  • Experience with recurrent neural networks (RNNs)
  • Experience with large language models (LLMs)
  • Experience with retrieval-augmented generation (RAG)
  • Strong understanding of vector-based retrieval methods and various NLP domains

Day to day

  • Use statistical, algorithmic, mining, and visualization techniques to model complex problems, discover insights, and identify opportunities. Lead initiatives to design, test, and implement predictive models and machine-learning algorithms. Collaborate with the Data Science Team Lead to prioritize business and information needs. Manage end-to-end data projects, ensuring they adhere to timelines and quality standards.
  • Work closely with product, engineering, and operational teams to contribute to cross-functional projects. Communicate predictive insights and recommendations to both technical and non-technical stakeholders. Act as a mentor to junior data scientists and analysts. Share knowledge and help team members enhance their skills in data science techniques and tools.