Senior Data Scientist

fully flexible
Work set-up: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

Minimum 5 years of experience in Data Science or Applied Machine Learning., Strong proficiency in Python, SQL, and ML libraries such as Pandas, Scikit-learn, TensorFlow, and PyTorch., Experience with big data platforms like Hadoop and Spark, and distributed data processing., Hands-on experience deploying machine learning models into production systems..

Key responsibilities:

  • Design, build, and deploy scalable machine learning models into production systems.
  • Develop advanced analytics and predictive models using Python, SQL, and ML frameworks.
  • Leverage big data technologies like Databricks, Spark, and Hadoop for data processing and model training.
  • Collaborate with engineering teams to integrate models into cloud-based applications on AWS.

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Proximity Works Scaleup https://www.proximity.tech/
51 - 200 Employees
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Job description

We’re seeking a highly skilled, executionfocused Senior Data Scientist with a minimum of 5 years of experience. This role demands handson expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving datadriven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problemsolving ability, and ownership in delivering business impact through data science.

Responsibilities

  • Design, build, and deploy scalable machine learning models into production systems.
  • Develop advanced analytics and predictive models using Python, SQL, and popular MLDL frameworks (Pandas, Scikitlearn, TensorFlow, PyTorch).
  • Leverage Databricks, Apache Spark, and Hadoop for largescale data processing and model training.
  • Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
  • Collaborate with engineering teams to integrate models into cloudbased applications on AWS.
  • Optimize query performance, storage usage, and data pipelines for efficiency.
  • Conduct endtoend experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
  • Drive initiatives independently with high ownership and accountability.
  • Stay up to date with industry best practices in machine learning, big data, and cloudnative deployments.
    • Requirements

      • Minimum 5 years of experience in Data Science or Applied Machine Learning.
      • Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikitlearn, TensorFlow, PyTorch).
      • Proven expertise in deploying ML models into production systems.
      • Experience with big data platforms (Hadoop, Spark) and distributed data processing.
      • Handson experience with Databricks, Airflow, and AWS EMR.
      • Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
      • Solid understanding of query optimization, storage systems, and data pipelines.
      • Excellent problemsolving skills, with the ability to design scalable solutions.
      • Strong communication and collaboration skills to work in crossfunctional teams.
        • Benefits

          • Best in class salary: We hire only the best, and we pay accordingly.
          • Proximity Talks: Meet other designers, engineers, and product geeks — and learn from experts in the field.
          • Keep on learning with a worldclass team: Work with the best in the field, challenge yourself constantly, and learn something new every day.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Collaboration
  • Communication
  • Problem Solving

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