Data Scientist in Stratford-upon-Avon

Data Scientist in Stratford-upon-Avon

Stratford-upon-Avon Full-Time No working from home possible
Z

Talent Acquisition Executive - UK/Europe at Zensar Technologies We are seeking an experienced Data Scientist to design, develop, and deploy advanced AI/ML models leveraging client pricing datasets. The ideal candidate will have a strong background in statistical modeling, machine learning, and data engineering, with proven experience in building scalable solutions for pricing optimization and predictive analytics.

Key Responsibilities

  • Design and implement AI/ML models for pricing optimization, elasticity analysis, and revenue forecasting.
  • Apply advanced algorithms (e.g., regression, tree-based models, deep learning) to large-scale pricing datasets.

Data Analysis & Feature Engineering

  • Perform exploratory data analysis (EDA) to identify patterns and anomalies in pricing data.
  • Develop robust feature engineering pipelines for model accuracy and interpretability.

Deployment & Integration

  • Collaborate with engineering teams to deploy models into production environments.
  • Ensure scalability, performance, and compliance with client requirements.

Stakeholder Collaboration

  • Work closely with pricing analysts, business teams, and client stakeholders to translate business objectives into data-driven solutions.
  • Present insights and recommendations through clear visualizations and reports.

Required Skills & Qualifications Education: Degree in Data Science, Computer Science, Statistics, or related field. Technical Expertise

  • Strong proficiency in Python, R, and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Experience with pricing analytics, predictive modeling, and optimization techniques.
  • Hands-on experience with SQL, big data platforms (Spark, Hadoop), and cloud services (AWS, Azure, GCP).
  • Deep understanding of pricing strategies, elasticity modeling, and revenue management.
  • Excellent communication and stakeholder management skills.

Preferred Qualifications

  • Experience in Insurance.
  • Familiarity with MLOps and CI/CD pipelines for ML models.
  • Knowledge of generative AI or advanced NLP techniques for pricing insights.

Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology Industries: IT Services and IT Consulting

We are seeking an experienced Data Scientist to design, develop, and deploy advanced AI/ML models leveraging client pricing datasets. The ideal candidate will have a strong background in statistical modeling, machine learning, and data engineering, with proven experience in building scalable solutions for pricing optimization and predictive analytics., Education: Degree in Data Science, Computer Science, Statistics, or related field. Technical Expertise

  • Strong proficiency in Python, R, and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Experience with pricing analytics, predictive modeling, and optimization techniques.
  • Hands-on experience with SQL, big data platforms (Spark, Hadoop), and cloud services (AWS, Azure, GCP).
  • Deep understanding of pricing strategies, elasticity modeling, and revenue management.
  • Excellent communication and stakeholder management skills.
  • Experience in Insurance.
  • Familiarity with MLOps and CI/CD pipelines for ML models.
  • Knowledge of generative AI or advanced NLP techniques for pricing insights.

#J-18808-Ljbffr

Data Scientist in Stratford-upon-Avon employer: Zensar

At Zensar, we pride ourselves on being an exceptional employer that fosters a dynamic and collaborative work environment. As a Technical Support Engineer, you will not only enhance your technical skills but also enjoy ample opportunities for personal and professional growth, all while contributing to a culture that values creativity and innovation. Located in a vibrant area, our team thrives on the freedom to explore thoughtful solutions, ensuring that every day presents new challenges and rewards.

Z

Contact Details:

Zensar Recruitment Team