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An innovative company seeks a skilled Data Scientist to drive process automation through data analysis and model development. In this exciting role, you will leverage your expertise in machine learning and statistical techniques to create predictive models and integrate data solutions into automation systems. The position offers a fully remote working environment, competitive salary, and opportunities for professional growth in a dynamic and collaborative setting. If you are passionate about data science and eager to make a significant impact, this is the perfect opportunity for you.
Key Responsibilities
• Data Analysis: Analyze large datasets (structured and unstructured) to identify trends, patterns, and relationships that can provide meaningful insights for process automation.
• Model Development: Design, build, and validate predictive and prescriptive models using machine learning and statistical techniques to solve complex business problems.
• AI Integration: Collaborate with engineering and product teams to integrate data science solutions into existing automation systems, ensuring they align with business objectives.
• Data Visualization: Develop clear and compelling data visualizations and dashboards to communicate findings and recommendations to stakeholders and decision-makers.
• Collaboration: Work with cross-disciplinary teams (including automation engineers, business analysts, and product managers) to understand challenges and identify opportunities for data-driven improvements.
• Continuous Improvement: Stay current on industry trends and emerging technologies in data science and AI, and identify ways to implement best practices and innovative solutions within the organization.
Qualification:
• Education: Bachelors, Masters or PhD degree in Data Science, Statistics, Computer Science, Engineering, or a related field.
• Experience: Minimum of 5 years of industry experience in data science or related fields, with a proven track record of delivering impactful results.
Required Technical Skills:
• Proficiency in programming languages such as Python, R, or SQL.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of statistical analysis, predictive modeling, and data mining techniques.
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus.
What we Offer: