Machine Learning & Data Analytics Engineer
Take on a hands-on engineering contract focused on Python, SQL, and machine learning models. Leverage strong data skills to advance your career. Great for experienced analysts.
Überblick über das Stellenangebot
The Machine Learning & Data Analytics Engineer contract is a fixed-term opportunity lasting more than six months. This role places a strong emphasis on technical expertise and hands-on experience, especially with Python and SQL for data processing and model building. Being a contract job, it offers flexibility but requires readiness to deliver from the start.
Candidates should bring at least two years of real-world experience deploying machine learning solutions, as well as handling large datasets for business and technical analysis. The primary working environment blends in-office and remote collaboration (hybrid-style scheduling), supporting productivity and autonomy for specialist professionals.
This position does not specify salary or rates upfront, which is common for technical contract roles. However, it is structured to attract seasoned engineers who value challenging, impactful work over rigid, long-term employment.
Solid programming ability in Python and advanced data manipulation using tools like SASSQL will be important for excelling here. This contract is extendable based on performance and project needs, offering motivated engineers a chance for longer engagement.
Hauptverantwortlichkeiten
The daily work revolves around data modelling and analysis. Specifically, you’ll build and deploy machine learning models using Python, ensuring quality data ingestion and transformation through SQL and scripting.
Engineers are expected to handle exploratory data analysis (EDA), generating actionable insights from complex, often high-volume datasets. The focus is on merging, aggregating, and validating data efficiently across different business use cases.
Feature engineering, model training, and evaluating prediction accuracy are crucial parts of the job. Most work falls under traditional supervised learning rather than advanced generative AI or NLP tasks.
Collaboration with stakeholders for gathering technical and business requirements is typical, as is documenting work clearly for handoff and extension beyond the initial term.
Success will require staying current with best practices in data science as well as strong communication for team-oriented problem solving.
Vorteile
Candidates benefit from a technically rich role, leading independent projects within an established organization. The hybrid work setup allows for work-life balance.
This contract can help sharpen data engineering skills and offers exposure to modern machine learning workflows, which are highly valued in the current job market.
Downsides
One drawback is the lack of upfront salary information, which may hinder decision-making for some jobseekers. Contract roles can feel less secure than permanent jobs.
Additionally, the focus is on traditional ML tasks, so engineers looking exclusively for generative AI or deep NLP work may find the scope somewhat limited.
Endgültiges Urteil
The Machine Learning & Data Analytics Engineer contract is best suited to experienced professionals seeking a technically focused, flexible role. While there are uncertainties, particularly with pay structure, the potential to expand your track record and contribute meaningful solutions can make it an excellent career move for the right applicant.
