Principal Data Scientist
Location: Nottinghamshire (Hybrid 3days/week)
Salary: £80,(Apply online only) – £90,(Apply online only)

Are you ready to take the lead in shaping the future of data science? We are recruiting on behalf of an exciting organisation for a Principal Data Scientist role based in Nottinghamshire. This is a hybrid position that offers the chance to combine hands-on technical work with strategic leadership, driving transformative business outcomes through data.

You’ll oversee the development of advanced analytics, machine learning models, and AI-driven solutions while collaborating with cross-functional teams to solve complex business challenges. This opportunity is the first lead hire for our clients data team so an exciting opportunity to make an impact.

Key Responsibilities

Shape and implement the organisation’s data science strategy, ensuring alignment with business objectives.
Provide thought leadership in machine learning and advanced analytics, guiding teams and influencing decision-making at the executive level.
Stay ahead of industry trends, positioning the organisation as a leader in data-driven innovation.

Design and deliver machine learning models, optimisation algorithms, and predictive analytics tools.
Lead full lifecycle projects, from data collection and preprocessing to model development, testing, and deployment.
Explore and deploy cutting-edge methods, including deep learning, natural language processing (NLP), and reinforcement learning.

Partner with data engineering teams to create scalable and reliable data pipelines.
Work closely with product, engineering, and business units to identify and capitalise on opportunities for innovation.
Simplify complex data science findings into actionable insights for diverse stakeholders.

What We’re Looking For

Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.
Experienced in data science or machine learning, with proven experience leading impactful projects.
Expertise in driving data science initiatives with measurable business outcomes.
Technical Skills:

Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Advanced knowledge of programming languages such as Python, R, or Scala.
Experience working with large-scale data platforms (e.g., Spark, Snowflake, Hadoop).
Hands-on expertise with cloud services like AWS, Azure, or GCP.
Strong analytical skills with a deep understanding of statistics and optimisation techniques.
Outstanding communication skills to bridge technical concepts and business objectives effectively.
Preferred Qualifications

Experience with advanced AI techniques such as NLP, deep learning, or reinforcement learning.
Knowledge of MLOps principles and tools (e.g., MLflow, Kubeflow).
Demonstrated contributions to peer-reviewed publications or open-source projects.

For more information on this role or other similar roles please contact Mae Fitzgerald

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