Data Scientist

Company Overview A leading international technology solutions company delivering innovative software, digital solutions, automation technologies, process equipment, measurement systems, and engineering services across multiple industries worldwide. Job Summary The Data Scientist leads data integration and analysis efforts, develops predictive models, and delivers actionable insights to enhance business performance and innovation through collaboration with software developers and cross-functional teams. Responsibilities Extract and integrate data from internal systems, APIs, and third-party sources to support digital solutions and analytics Maintain and optimize databases to ensure efficient data analysis and retrieval Cleanse, validate, and preprocess structured and unstructured datasets to prepare for analysis Perform exploratory data analysis to identify patterns, trends, and anomalies that inform business decisions Develop predictive models using statistical, machine learning, and AI techniques to forecast outcomes and support strategic initiatives Apply regression, classification, clustering, decision trees, and neural networks appropriately to solve complex problems Validate and optimize models through cross-validation, hyperparameter tuning, and rigorous testing to ensure accuracy and reliability Develop production-ready data applications and analytics solutions that integrate seamlessly with business processes Create dashboards and reports using Tableau, Power BI, Python, or similar tools to visualize data insights for stakeholders Collaborate with business and technical stakeholders to identify and solve business challenges using data-driven approaches Align data science initiatives with organizational objectives to drive measurable business impact Stay current with emerging trends and advancements in data science, AI, and analytics to continuously improve capabilities Preferred competencies and qualifications Proficiency in Python, R, and SQL for data manipulation, analysis, and model development Experience with Pandas, NumPy, and machine learning frameworks such as Scikit-learn, TensorFlow, or Keras to build and deploy models Knowledge of Tableau, Power BI, or equivalent visualization tools to create impactful data presentations Exposure to cloud platforms such as AWS, Azure, or Google Cloud for scalable data processing and storage Strong grounding in statistics, probability, and mathematical modeling to underpin analytical methods Manufacturing or industrial analytics experience to apply data science in relevant industry contexts Degree in Computer Science, Statistics, Mathematics, Engineering, or a related discipline Minimum 2–5 years’ experience in data science, analytics, or related fields with hands-on experience handling large datasets and machine learning projects Passion for continuous learning and ability to work independently with minimal supervision Strong attention to detail, curiosity, and willingness to travel occasionally Comfortable working with regional and global stakeholders