Data Architect - (Ai/Ml)

As a Data Architect-AI/ML at our company, you will play a crucial role in analyzing large payment datasets to uncover actionable insights, build predictive models, and contribute to strategic decision-making across various departments. Your responsibilities will include: - Analyzing and interpreting complex financial data to identify trends, patterns, and actionable insights. - Developing and implementing machine learning models for predictive analytics, classification, regression, etc. - Collaborating with product, engineering, and business teams to define data science requirements and deliver impactful results. - Cleaning, preprocessing, and transforming data to ensure quality and consistency. - Using data visualization techniques to communicate findings clearly to non-technical stakeholders. - Contributing to the development and enhancement of data pipelines and workflows. - Monitoring and evaluating model performance, ensuring accuracy and reliability over time. - Staying updated on the latest advancements in data science and machine learning. Qualifications required for this role include: - 10-15 years of hands-on experience in artificial intelligence, data science, machine learning, or related fields. - Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. In terms of technical skills and efficiency, you should have: - Proficiency in Python, R, or similar programming languages for data analysis and model development. - Strong knowledge of machine learning algorithms (e.g., regression, classification, clustering). - Familiarity with data manipulation and analysis libraries (e.g., pandas, NumPy, SciPy). - Familiarity with AWS cloud platforms (DMR, Glue, Redshift). - Experience with data visualization tools (e.g., Tableau, Power BI, superset). - Experience working with large datasets and performing data cleaning and preprocessing. - Strong communication skills and ability to collaborate with cross-functional teams. Preferred skills include familiarity with: - Development tools (e.g., Jupyter notebook, visualBasic code). - SQL databases. - Deep learning frameworks (e.g., TensorFlow, PyTorch). - Data processing tools (e.g., Spark). - Version control systems like Git. In addition to technical skills, we value the following qualities in our team members: - Excellent verbal and written communication skills. - Ability to build relationships with candidates and stakeholders. - Strong organizational skills to manage multiple roles and priorities in a fast-paced environment. - Comfort with dynamic requirements and the ability to pivot recruitment strategies as needed. As part of our team, you should be comfortable with: - Working from the office, 5 days a week. - Pushing boundaries and bringing innovative ideas to the table. - Embracing out-of-the-box thinking and taking ownership of your work. If you are someone who decides fast, takes ownership, seeks to learn, and takes pride in your work, you will be a valuable addition to our team. As a Data Architect-AI/ML at our company, you will play a crucial role in analyzing large payment datasets to uncover actionable insights, build predictive models, and contribute to strategic decision-making across various departments. Your responsibilities will include: - Analyzing and interpreting complex financial data to identify trends, patterns, and actionable insights. - Developing and implementing machine learning models for predictive analytics, classification, regression, etc. - Collaborating with product, engineering, and business teams to define data science requirements and deliver impactful results. - Cleaning, preprocessing, and transforming data to ensure quality and consistency. - Using data visualization techniques to communicate findings clearly to non-technical stakeholders. - Contributing to the development and enhancement of data pipelines and workflows. - Monitoring and evaluating model performance, ensuring accuracy and reliability over time. - Staying updated on the latest advancements in data science and machine learning. Qualifications required for this role include: - 10-15 years of hands-on experience in artificial intelligence, data science, machine learning, or related fields. - Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. In terms of technical skills and efficiency, you should have: - Proficiency in Python, R, or similar programming languages for data analysis and model development. - Strong knowledge of machine learning algorithms (e.g., regression, classification, clustering). - Familiarity with data manipulation and analysis libraries (e.g., pandas, NumPy, SciPy). - Familiarity with AWS cloud platforms (DMR, Glue, Redshift). - Experience with data visualization tools (e.g., Tableau, Power BI, superset). - Experience working with large datasets and performing data cleaning and preprocessing. - Strong communication skil