Instrumentel is a world-leading provider of asset monitoring solutions for precision measurement in extreme environments. Our solutions include Condition-Based Predictive Maintenance, Condition Monitoring of remote assets and predictive analytics to improve asset performance.
We are now looking to recruit a Data Scientist to join our busy team in Leeds. As a Data Scientist at Instrumentel, you will leverage your analytical skills and technical expertise to develop innovative data-driven solutions. You will work with cross-functional teams to extract meaningful insights from complex datasets, build robust machine learning models, and deploy scalable solutions that address critical business challenges across a variety of industries, including rail, manufacturing, sustainability, and FMCG.
Key responsibilities of the role will include:
Data Analysis and Modeling: Develop and apply advanced statistical and machine learning techniques to analyze large and complex datasets. Feature Engineering: Extract meaningful features from diverse data sources, including time-series, sensor data, and image data. Model Development and Deployment: Build, train, and deploy predictive models to identify patterns, anomalies, and actionable insights. Machine Learning Operations (MLOps): Collaborate with teams to implement robust MLOps pipelines for model deployment, monitoring, and retraining. Data Visualisation / Story Telling: Create clear and impactful data visualisations to communicate findings to both technical and non-technical audiences, using methods such as data story telling and interactive communication tools (i.e. plotly) Machine Vision: Apply computer vision techniques, e.g. object detection, instance segmentation, OCR, to analyse images and videos, enabling the detection of defects, anomalies, and operational inefficiencies. Domain Expertise: Collaborate with industry experts and customers to gain a deep understanding of business challenges and requirements, and translate them into actionable data-driven solutions. Innovation and Research: Stay up-to-date with the latest advancements in data science and machine learning, and contribute to research and development initiatives. Collaboration: Work closely with cross-functional teams, including engineers, product managers, and domain experts, to deliver impactful solutions. The successful candidate will be qualified to Degree level in Mathematics, Computer Science, Statistics, Physics, or a similarly quantitative field. Candidates must also be able to demonstrate the following skills and experience
Experience in statistical modeling, machine learning, data mining, unstructured data analytics, natural language processing. Proficiency in statistical and other tools/direct coding languages, e.g., Python, R, SQL. Familiarity with relational databases and intermediate-level knowledge of SQL. Sound understanding of a wide range of statistical techniques. Advanced analytical techniques, e.g., regression analysis, predictive analysis, data mining. Agile Methodologies. Experience in data mining/feature selection. Understanding of machine learning/predictive modeling. Excellent communication skills (both written and verbal). High self-motivation and ability to work autonomously. Excellent interpersonal skills dealing with stakeholders at all levels within the organization. Experience with computer vision techniques (e.g., image classification, object detection). Ability to work with large datasets and complex data pipelines. Ability to translate business requirements into technical solutions. In addition to the above experience, candidates must be able to demonstrate a strong analytical mind and a keen eye for detail, the ability to work independently and as part of a team, a passion for learning and staying up-to-date with the latest trends in data science and machine learning and a strong work ethic with a commitment to delivering high-quality work.#J-18808-Ljbffr