AI/ML Solution Lead, Data Science

As an AI Solutions Architect with around 10-15 years of experience, including at least 5-8 years in relevant data science, analytics, and AI/ML, your role will involve developing strategies and solutions to solve problems creatively using cutting-edge machine learning, deep learning, and GEN AI techniques. You will lead a team of data scientists to ensure timely and high-quality delivery of project outcomes. Your responsibilities will include: - Identifying and addressing client needs across various domains by analyzing large and complex data sets, processing and verifying data integrity, and performing exploratory data analysis (EDA) using advanced methods. - Selecting features, building, and optimizing classifiers/regressors with machine learning and deep learning techniques. - Enhancing data collection procedures to ensure relevance for analytical systems and maintaining data accuracy. - Conducting ad-hoc analyses and presenting clear results to both technical and non-technical stakeholders. - Creating custom reports and presentations with strong data visualization and storytelling skills to effectively communicate analytical conclusions to senior company officials and other stakeholders. - Demonstrating expertise in data mining, EDA, feature selection, model building, and optimization using machine learning and deep learning techniques. - Utilizing strong programming skills in Python. - Exhibiting excellent communication and interpersonal skills to convey complex analytical concepts to a diverse audience. Your primary skills should include: - Solid understanding and hands-on experience in data science and machine learning techniques and algorithms for supervised and unsupervised problems, NLP, computer vision, and GEN AI. Proficiency in applied statistics skills such as distributions, statistical inference, and testing. - Experience in building deep-learning models for text and image analytics, including ANNs, CNNs, LSTM, Transfer Learning, Encoder, and decoder. - Proficiency in coding with common data science languages and tools like R and Python. - Familiarity with data science toolkits such as NumPy, Pandas, Matplotlib, StatsModel, Scikitlearn, SciPy, NLTK, Spacy, OpenCV, etc. - Experience with frameworks like Tensorflow, Keras, PyTorch, XGBoost, etc. - Exposure or knowledge in cloud platforms such as Azure and AWS. - Experience in deploying models in production environments. Additionally, you should have standard skills including: - In-depth understanding of manufacturing workflows, production planning, and quality control. - Familiarity with ISA-95 and ISA-88 standards for manufacturing systems. - Experience working with shop floor automation and IoT devices. Good to have skills would include: - MES Certifications, regulatory experience, and knowledge of emerging technologies like IoT or edge computing. As an AI Solutions Architect with around 10-15 years of experience, including at least 5-8 years in relevant data science, analytics, and AI/ML, your role will involve developing strategies and solutions to solve problems creatively using cutting-edge machine learning, deep learning, and GEN AI techniques. You will lead a team of data scientists to ensure timely and high-quality delivery of project outcomes. Your responsibilities will include: - Identifying and addressing client needs across various domains by analyzing large and complex data sets, processing and verifying data integrity, and performing exploratory data analysis (EDA) using advanced methods. - Selecting features, building, and optimizing classifiers/regressors with machine learning and deep learning techniques. - Enhancing data collection procedures to ensure relevance for analytical systems and maintaining data accuracy. - Conducting ad-hoc analyses and presenting clear results to both technical and non-technical stakeholders. - Creating custom reports and presentations with strong data visualization and storytelling skills to effectively communicate analytical conclusions to senior company officials and other stakeholders. - Demonstrating expertise in data mining, EDA, feature selection, model building, and optimization using machine learning and deep learning techniques. - Utilizing strong programming skills in Python. - Exhibiting excellent communication and interpersonal skills to convey complex analytical concepts to a diverse audience. Your primary skills should include: - Solid understanding and hands-on experience in data science and machine learning techniques and algorithms for supervised and unsupervised problems, NLP, computer vision, and GEN AI. Proficiency in applied statistics skills such as distributions, statistical inference, and testing. - Experience in building deep-learning models for text and image analytics, including ANNs, CNNs, LSTM, Transfer Learning, Encoder, and decoder. - Proficiency in coding with common data science languages and tools like R and Python. - Familiarity with data science toolk