Remote LTK - Sr. Data Scientist - 166

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.
• Responsibilities include designing, developing, and implementing robust machine learning models tailored to solve complex business problems and improve product offerings.
• The candidate will utilize AI technologies to analyze large and diverse datasets, uncovering trends, patterns, and insights that inform strategic decision-making.
• Collaboration with cross-functional teams including product managers, engineers, and analysts is essential to translate business requirements into scalable data science solutions.
• The role involves leading the end-to-end lifecycle of AI model deployment, ensuring models are production-ready, maintainable, and performant within cloud environments.
• Conducting rigorous statistical modeling and data analysis to validate model assumptions, evaluate performance, and optimize algorithms is required.
• The candidate will develop and maintain data visualization tools and dashboards to communicate findings effectively to both technical and non-technical stakeholders.
• Mentoring junior data scientists and contributing to building a culture of continuous learning and innovation within the data science team is expected.
• Staying current with the latest advancements in machine learning, AI, and data science methodologies to continuously enhance LTK’s data capabilities is crucial.
• Collaboration with data engineering teams to ensure data quality, availability, and efficient data pipelines that support machine learning workflows is necessary.
• Participation in defining best practices for data science processes, including model governance, reproducibility, and ethical AI considerations is part of the role.
• Proven expertise in designing, building, and deploying machine learning models using supervised, unsupervised, and reinforcement learning techniques is essential.
• Advanced proficiency in Python programming, including libraries such as scikit-learn, TensorFlow, PyTorch, and pandas for data manipulation, model development, and experimentation is required.
• Strong analytical skills to interpret complex datasets, perform exploratory data analysis, and derive meaningful insights that drive business value are critical.
• A deep understanding of statistical concepts and methods, including regression, classification, time series analysis, and probabilistic modeling to support robust data-driven conclusions is necessary.
• Expertise in creating compelling visualizations using tools like Matplotlib, Seaborn, or equivalent to effectively communicate data insights and model results to diverse audiences is expected.
• Experience deploying AI and machine learning models into production environments, ensuring scalability, reliability, and integration with existing systems is required.
• Familiarity with containerization and orchestration technologies is a plus.
• Proficiency 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 is necessary.

Requirements:

• The candidate must have over five years of hands-on experience in machine learning, data analysis, and AI model deployment, primarily using Python.
• Proven expertise in designing, building, and deploying machine learning models using supervised, unsupervised, and reinforcement learning techniques is essential.
• Advanced proficiency in Python programming, including libraries such as scikit-learn, TensorFlow, PyTorch, and pandas for data manipulation, model development, and experimentation is required.
• Strong analytical skills to interpret complex datasets, perform exploratory data analysis, and derive meaningful insights that drive business value are critical.
• A deep understanding of statistical concepts and methods, including regression, classification, time series analysis, and probabilistic modeling to support robust data-driven conclusions is necessary.
• Expertise in creating compelling visualizations using tools like Matplotlib, Seaborn, or equivalent to effectively communicate data insights and model results to diverse audiences is expected.
• Experience deploying AI and machine learning models into production environments, ensuring scalability, reliability, and integration with existing systems is required.
• Proficiency 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 is necessary.

Benefits:

• The position offers the opportunity to work in a dynamic team environment that fosters innovation and continuous learning.
• Employees will have the chance to mentor junior data scientists and contribute to a culture of knowledge sharing.
• The role allows for collaboration with cross-functional teams, enhancing professional growth and exposure to various business areas.
• The company supports staying current with the latest advancements in machine learning, AI, and data science methodologies.
• Employees will have access to advanced tools and technologies to enhance their data capabilities and project outcomes.