LTK - Sr. Data Scientist - 166

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August 15

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Thaloz

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SaaS • B2B • Enterprise

Thaloz is a tech consulting and outsourcing company focused on cloud-native product development and engineering team outsourcing. They offer tailored software development solutions, leveraging top-tier talent from Latin America. Thaloz provides a variety of services such as custom product development, staff augmentation, and enterprise solutions. Their approach emphasizes people-focused consulting and remote work culture, ensuring seamless integration of skilled IT professionals into their clients' projects. With expertise in diverse technologies, Thaloz offers end-to-end support from strategy to launch, fostering smooth communication and collaboration.

51 - 200 employees

☁️ SaaS

🤝 B2B

🏢 Enterprise

📋 Description

• We are seeking a highly skilled and experienced Senior Data Scientist to our dynamic team. This role is pivotal in driving the company’s data-driven initiatives by developing and deploying advanced machine learning models and leveraging AI technologies to extract actionable insights from complex datasets. The ideal candidate will bring over five years of hands-on experience in machine learning, data analysis, and AI model deployment, primarily using Python. • Design, develop, and implement robust machine learning models tailored to solve complex business problems and improve product offerings. • Utilize AI technologies to analyze large and diverse datasets, uncovering trends, patterns, and insights that inform strategic decision-making. • Collaborate with cross-functional teams including product managers, engineers, and analysts to translate business requirements into scalable data science solutions. • Lead the end-to-end lifecycle of AI model deployment, ensuring models are production-ready, maintainable, and performant within cloud environments. • Conduct rigorous statistical modeling and data analysis to validate model assumptions, evaluate performance, and optimize algorithms. • Develop and maintain data visualization tools and dashboards to communicate findings effectively to both technical and non-technical stakeholders. • Mentor junior data scientists and contribute to building a culture of continuous learning and innovation within the data science team. • Stay current with the latest advancements in machine learning, AI, and data science methodologies to continuously enhance LTK’s data capabilities. • Collaborate with data engineering teams to ensure data quality, availability, and efficient data pipelines that support machine learning workflows. • Participate in defining best practices for data science processes, including model governance, reproducibility, and ethical AI considerations.

🎯 Requirements

• Proven expertise in designing, building, and deploying machine learning models using supervised, unsupervised, and reinforcement learning techniques. Experience with model selection, feature engineering, hyperparameter tuning, and performance evaluation is essential. • Advanced proficiency in Python programming, including libraries such as scikit-learn, TensorFlow, PyTorch, and pandas for data manipulation, model development, and experimentation. Ability to write clean, efficient, and well-documented code. • Strong analytical skills to interpret complex datasets, perform exploratory data analysis, and derive meaningful insights that drive business value. Experience with statistical testing and hypothesis validation is critical. • Deep understanding of statistical concepts and methods, including regression, classification, time series analysis, and probabilistic modeling to support robust data-driven conclusions. • Expertise in creating compelling visualizations using tools like Matplotlib, Seaborn, or equivalent to effectively communicate data insights and model results to diverse audiences. • Experience deploying AI and machine learning models into production environments, ensuring scalability, reliability, and integration with existing systems. Familiarity with containerization and orchestration technologies is a plus. • Proficient in SQL for querying and managing relational databases, optimizing queries, and working with large datasets stored in systems such as MySQL, PostgreSQL, or Microsoft SQL Server.