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- Tasks: Design and deploy advanced AI/ML models for pricing optimisation and predictive analytics.
- Company: Join Zensar Technologies, a leader in IT services and consulting.
- Benefits: Enjoy competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make an impact with cutting-edge technology while collaborating with diverse teams.
- Qualifications: Degree in Data Science or related field; strong skills in Python and ML libraries.
- Other info: Dynamic work environment with excellent career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
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.
- Perform exploratory data analysis (EDA) to identify patterns and anomalies in pricing data.
- Develop robust feature engineering pipelines for model accuracy and interpretability.
- Collaborate with engineering teams to deploy models into production environments.
- Ensure scalability, performance, and compliance with client requirements.
- 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.
- 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
Data Scientist in Stratford-upon-Avon employer: Zensar Technologies
Contact Detail:
Zensar Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Stratford-upon-Avon
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, attend meetups, and join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those related to pricing analytics. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with stakeholders who may not be data-savvy.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Scientist in Stratford-upon-Avon
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with AI/ML models, pricing analytics, and any relevant projects that showcase your skills in Python, R, and SQL.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your background aligns with the responsibilities listed in the job description. Be specific!
Showcase Your Projects: If you've worked on any relevant projects, whether in a professional setting or as personal endeavours, make sure to mention them. Include links to your GitHub or portfolio to give us a taste of your work.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at Zensar Technologies
✨Know Your Data Inside Out
Before the interview, dive deep into the datasets you might be working with. Familiarise yourself with common pricing strategies and how data can influence them. Being able to discuss specific examples of your past work with data analysis and feature engineering will show your expertise.
✨Brush Up on Your Technical Skills
Make sure you're comfortable with Python, R, and the relevant ML libraries like scikit-learn and TensorFlow. Be prepared to discuss your experience with SQL and big data platforms. You might even want to practice coding problems or model-building scenarios to demonstrate your skills during the interview.
✨Prepare for Stakeholder Scenarios
Think about how you've collaborated with business teams in the past. Prepare examples where you translated complex data insights into actionable recommendations. This will highlight your communication skills and ability to work with stakeholders, which is crucial for this role.
✨Visualisation is Key
Since presenting insights is part of the job, practice creating clear and impactful visualisations. Bring examples of your previous work that showcase your ability to communicate data-driven insights effectively. This will help you stand out as a candidate who can not only analyse data but also convey its importance to others.
