Applied Data Scientist

Voltaware Services Limited; United Kingdom; On-site; GBP 60,000 - 90,000; Full time

Job summary

A leading machine learning company in the UK seeks an experienced Applied Data Scientist to innovate and deploy machine learning models. The successful candidate will have an advanced degree and extensive background in machine learning research, with at least 5 years of hands-on experience. Key responsibilities include developing algorithms, implementing ML models in production, and defining KPIs to measure success. This position offers competitive compensation and a collaborative work environment.

Benefits

Competitive salary

Professional development opportunities

Possible stock option plan

Qualifications

• 5+ years of experience in machine learning with proven results.
• Expertise in machine learning algorithms and deep learning frameworks.
• Familiarity with big data technologies like Spark or Hadoop.

Responsibilities

• Develop learning algorithms aligned with business objectives.
• Implement data science techniques in production environments.
• Define and measure success through well-constructed KPIs.

Skills

Machine learning research

Python programming

MLOps practices

Statistical modeling

Education

Master's or Ph.D. in Computer Science or related field

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Spark

Job description

Job Description

We are seeking an experienced and hands‑on Applied Data Scientist to drive our Machine Learning team. This role is critical in driving innovation, discovering cutting‑edge ML algorithms, and ensuring the successful deployment of models into production. The ideal candidate will have a strong background in machine learning research, hands‑on experience with production‑grade ML systems, and the ability to define and measure success through well‑constructed KPIs.

Key Responsibilities

• Own the development of learning algorithms and techniques aligned with business objectives.
• Solve real‑world business problems by implementing data science techniques, algorithms, and machine learning models into production environments.
• Partner with product managers to define the strategy and roadmap for the ML Applied team in alignment with the company's goals.
• Oversee the end‑to‑end lifecycle of ML models, from research and prototyping to production deployment.
• Ensure the team develops scalable, efficient, and reliable tooling for deploying and monitoring ML models in production environments.
• Work closely with other data engineers and software developers teams to integrate ML models into production via a unified Software Development Life Cycle.
• Define and implement key performance indicators (KPIs) to evaluate the performance and impact of ML models.
• Establish robust validation frameworks to ensure models meet business and technical requirements.
• Continuously monitor to improve and troubleshoot model performance post‑deployment.

Qualifications

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 5+ years of experience in machine learning research and development, with a proven track record of delivering impactful solutions.
• Strong expertise in ML algorithms, statistical modeling, and deep learning frameworks (e.g., TensorFlow, PyTorch, Scikit‑learn).
• Proficiency in Python programming language.
• Experience with MLOps practices, tools, and frameworks (e.g., MLflow, Kubeflow, Docker, CI/CD pipelines).
• Familiarity with big data technologies (e.g., Spark, Hadoop) and data engineering workflows.

Bonus

• Familiarity with electricity fundamentals and signal processing applied to energy data, feature extraction from waveforms, event detection, and load disaggregation for real‑world consumption monitoring.

What We Offer

• Competitive salary and benefits package.
• Opportunity to work on cutting‑edge ML research and impactful real‑world applications.
• Possible stock option plan, subject to performance review.
• A collaborative and inclusive work environment that values innovation and creativity. Professional development opportunities, including conferences, workshops, and training.

Location

Product Owner - UK