National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Scientist

Pepperjam
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Who We Are:

The partnership channel offers scale and automation on a pay-for-performance model that delivers the operating leverage necessary for brand survival. Partnerize empowers marketers with technology built to discover, engage, and convert audiences, at scale, all while maintaining brand safety and control.

Why Join Us?

Our commitment to growing partnerships doesn't end with our clients. Our employees are carefully selected to be a part of our company because they emulate a carefully crafted and practiced set of core values that define us and our business. Joining Partnerize means joining a company that sincerely values your talent, expertise, and passion. We strive each day to hire and retain only the best. Doing so affords us the opportunity to be the best in the business, to exceed our clients' expectations, to innovate, to teach—and most importantly—to earn and maintain our clients’ loyalty.

The things you care about

At the heart of our platform, we track performance marketing data and build solutions to turn this data into useful information for our customers. We work with a lot of data, generating over a billion events across our infrastructure daily. We aim to make as much of this data available in real-time as possible, which is no mean feat at this scale!

We are looking for a highly skilled Data Scientist to join our team. The ideal candidate should have extensive experience in data exploration, machine learning, Python, SQL, Spark, and version control using Git.

As a Senior Data Scientist at Partnerize, you will:

Lead the end-to-end development and deployment of machine learning models into production, from data exploration and feature engineering to model training, evaluation, and monitoring. Collaborate with cross-functional teams to understand business requirements, identify opportunities for leveraging machine learning, and define success criteria for model performance. Apply machine learning techniques to solve complex problems, such as classification, forecasting, clustering, and recommendation, across diverse domains. Utilize Python programming and data engineering skills to preprocess and analyze large datasets, using tools such as Spark and Pandas. Containerize machine learning models for efficient deployment and scaling. Design and optimize SQL queries to extract and manipulate data from relational databases, ensuring data quality and integrity. Monitor model performance and health in production, and implement strategies for model retraining, tuning, and updating as needed. Mentor and coach junior data scientists, and contribute to the continuous learning and development of the data science team. Exhibit strong communication and presentation skills, with the ability to effectively communicate technical concepts to non-technical stakeholders and influence decision-making.

You are a Senior Data Scientist with:

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. 5+ years of experience in data science roles, with a focus on building and deploying machine learning models into production. Proficiency in Python programming and libraries such as NumPy, Pandas, Scikit-learn, and TensorFlow or PyTorch for machine learning. Experience with distributed computing frameworks such as Spark for processing large-scale datasets. Strong knowledge of containerization technologies such as Docker  Proficiency in SQL and experience working with relational databases such as PostgreSQL, MySQL, or BigQuery. Experience with data visualization tools such as Matplotlib, Seaborn, Plotly, or Tableau. Experience using API frameworks such as Flask or Fast API Strong problem-solving and analytical skills, with a proven track record of delivering impactful solutions to complex business problems. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and influence decision-making.

We hope you have:

Experience working in Agile or DevOps environments, with a focus on CI/CD practices and automation. Familiarity with distributed query engines, such as Druid, and experience optimizing queries for performance.

At the heart of our platform, we track performance marketing data and build solutions to turn this data into useful information for our customers. We work with a lot of data, generating over a billion events across our infrastructure daily. We aim to make as much of this data available in real-time as possible, which is no mean feat at this scale!

We are looking for a highly skilled Senior Data Engineer to join our team. The ideal candidate should have extensive experience with Google Cloud Platform, Google BigQuery, Apache Airflow, Airbyte, HDFS, Apache Spark, and Hive.

As a Senior Data Engineer at Partnerize, you will:

Design, build, and maintain data pipelines using Google Cloud Platform, Google BigQuery, Apache Airflow, Airbyte, HDFS, Kafka and Apache Spark Integrate large sets of data from numerous internal and external sources Ensure the reliability and performance of data systems by implementing best practices for data quality, security, and scalability Collaborate with cross-functional teams to understand business objectives and translate them into technical solutions Collaborate with data scientists and other stakeholders to support data-driven decision making and implement data solutions Design and implement data models and explain trade-offs of different modeling approaches Stay up to date with the latest developments and technologies in the data engineering field

You are a data engineer with:

Strong experience with Google Cloud Platform, Google BigQuery, Apache Airflow, Airbyte, HDFS, and Apache Spark Experience with data warehousing, data modeling, and ETL data pipelines design, implementation, and maintenance Good knowledge of software engineering practices and hands-on experience with writing Python production-level code Good knowledge of SQL and approaches to query optimization Strong understanding of data security and privacy principles Excellent problem-solving and critical thinking skills Strong communication and collaboration skills

We hope you have:

Good understanding of CI/CD Experience of working in an Agile environment and understanding of key agile practices Experience with data management for BI tools like Tableau

UK Benefits & Perks

25 days holiday in addition to bank holidays  Enhanced Parental Leave: 6 months full pay for birth parent, 4 weeks non-birth parent at full pay after one year employment 5 extra 'Partnerize Parental Days' each year Private Medical Insurance through Bupa  Enhanced pension contributions Cycle to Work scheme  Eye Care Vouchers  Life Assurance Enhanced Wellness Program including access to EAP, Wellness Coaching & Wellness Fridays program Regular company events and activities
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.