Senior Data and AI Specialist at Iota Impact | Torre
Senior Data and AI Specialist
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Iota Impact

Senior Data and AI Specialist

Iota Impact
Posted by
Heliana Andrea Agámez Rojas
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Emma
Emma
We make use of artificial intelligence and automation to turn complicated data into simple strategies.
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Full-time

Legal agreement: Employment

Compensation
COP6M - 8M/month
~USD1.64K - 2.19K/month
Negotiable
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Remote (for Colombia residents)
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Posted over 1 year ago

Requirements and responsibilities

🚀 Profile: Professional in engineering, economics, mathematics, physics, and/or related fields. With at least 5 years of demonstrable work experience in data analysis, artificial intelligence (AI), process automation, machine learning, and generating insights and visualizations for executive reports and dashboards. With proven ability to develop innovative products through the application of Generative AI. A person with high analytical and numerical capacity, excellent communication skills, great attention to detail, and proactive, passionate, and critical. 🚀 Requirements: 🔸English level: C1. 🔸Advanced level of Python focused on data analysis and Machine Learning. 🔸High analytical and numerical capacity with strong bases in statistics. 🔸Knowledge of data visualization tools. 🔸Knowledge in the application of Machine Learning Models such as clustering, classification, Regression and reinforcement learning. 🔸Basic knowledge of structured and unstructured database management languages. 🔸Intermediate knowledge of Excel. 🔸Experience in developing AI-based models and applications. Desirable: 🔸Knowledge and/or experience in BPM (Business Process Management). 🚀 Responsibilities: 🔸Data Analysis: Perform in-depth analysis of complex data sets to extract patterns, trends, and valuable insights. 🔸Model Development: Apply machine learning techniques to build, train, and evaluate predictive and descriptive models. 🔸Python Programming: Use advanced Python skills for efficient data manipulation, implementation of machine learning algorithms, and process automation. 🔸Statistics: Apply statistical principles to interpret data, validate results, and guarantee the robustness of the analyses. 🔸Data Visualization: Create clear and compelling visualizations to communicate findings in an understandable way to different audiences. 🔸Cross-functional collaboration: Work closely with engineering teams, businesses, and other stakeholders to understand requirements and provide analytical solutions. 🔸Process Optimization: Identify opportunities to improve the efficiency and quality of data management and analysis processes. 🔸Product Strategy Development: Define and develop product strategies that align customer needs with technological capabilities and business objectives.
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