4 Feature Selection Jobs

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Must have experience with Machine Learning Model Development. Expert Level Proficiency in Data Handling (SQL). Hands-on with Model Engineering and Improvement. Strong experience in Model Deployment and Productionalization. Extensive experience in developing and implementing machine learning, Deep Learning, NLP models across various domains. Strong proficiency in Python, including relevant libraries and frameworks for machine learning, such as scikit-learn, XGBoost, and Keras. Ability to write efficient, clean, and scalable code for model development and evaluation. Proven experience in enhancing model accuracy through engineering techniques, such as feature engineering, feature selection, and data augmentation. Ability to analyze model samples in relation to model scores, identify patterns, and iteratively refine models for improved performance. Strong expertise in deploying machine learning models to production systems. Familiarity with the end-to-end process of model deployment, including data preprocessing, model training, optimization, and integration into production environments. We recognise the significance of flexible work arrangements to provide support in a hybrid mode, you will get an environment to maintain a healthy work-life balance. Our focus will be your career growth & professional development to support you in exploring the world of opportunities. Equip yourself with valuable certifications & training programmes in the latest technologies such as AIML, Machine Learning. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.,

At Lilly, we are committed to uniting caring with discovery to enhance the quality of life for individuals worldwide. As a global healthcare leader headquartered in Indianapolis, Indiana, we have a workforce of 39,000 employees dedicated to developing and delivering life-changing medicines, advancing disease understanding and management, and contributing to our communities through philanthropic efforts. Our priority is always people, and we are in search of individuals who share our passion for making a positive impact on global well-being. As part of our ongoing efforts to achieve these goals, we are focused on building and internalizing a cutting-edge recommendation engine platform. This platform is designed to facilitate more agile sales and marketing operations by incorporating various data sources, implementing advanced personalization models, and seamlessly integrating with all other Lilly operations platforms. The ultimate aim is to provide tailored recommendations to sales and marketing teams at the individual doctor level, thereby enhancing decision-making processes and elevating customer experiences. Key Responsibilities: - Demonstrate a strong grasp of deep learning models to develop optimized Omnichannel Promotional Sequences for implementation by sales teams - Analyze extensive datasets to identify trends and insights that inform modeling decisions - Ability to translate business challenges into statistical problem statements, propose solution approaches, and consider relevant constraints - Collaborate with stakeholders to effectively communicate analysis findings - Proficiency in pharma datasets and industry knowledge is advantageous - Experience in code refactoring, training, retraining, deployment, testing, and monitoring of ML models for drift - Optimization of model hyperparameters - Willingness to learn new skills, particularly in ML applications for solving business problems Required Qualifications: - Bachelor's degree in Computer Science, Statistics, or related field preferred - 2-6 years of hands-on experience with data analysis, including coding, summarization, and interpretation - Proficient in coding languages like SQL or Python - Prior experience in deploying, evaluating performance, and fine-tuning recommendation engine models using ML techniques (e.g., CNN/LSTM, GA, XGBoost) for healthcare-related industries - Proficiency in Feature Engineering, Feature Selection, and Model Validation on Big Data - Familiarity with cloud technologies such as AWS, including tools like S3, EMR, EC2, Redshift, Glue; experience with visualization tools like Tableau and Power BI is a plus At Lilly, we are dedicated to fostering an inclusive workforce that provides equal opportunities for individuals with disabilities. If you require accommodations to apply for a position at Lilly, please complete the accommodation request form for further assistance. Please note that this form is specifically for accommodation requests related to the application process.,

As a data science expert, you will be responsible for developing strategies and solutions to address various problems using cutting-edge machine learning, deep learning, and GEN AI techniques. Your role will involve leading a team of data scientists to ensure timely and high-quality delivery of project outcomes. You will analyze large and complex datasets across different domains, perform exploratory data analysis, and select features to build and optimize classifiers and regressors. Enhancing data collection procedures, ensuring data quality and accuracy, and presenting analytical results to technical and non-technical stakeholders will be key aspects of your job. You will create custom reports and presentations with strong data visualization skills to effectively communicate analytical conclusions to senior company officials and other stakeholders. Proficiency in data mining, EDA, feature selection, model building, and optimization using machine learning and deep learning techniques is essential. Your primary skills should include a deep understanding and hands-on experience with data science and machine learning techniques, algorithms for supervised and unsupervised problems, NLP, computer vision, and GEN AI. You should also have expertise in building deep learning models for text and image analytics using frameworks like ANNs, CNNs, LSTM, Transfer Learning, Encoder, and decoder. Proficiency in programming languages such as Python, R, and common data science tools like NumPy, Pandas, Matplotlib, and frameworks like TensorFlow, Keras, PyTorch, XGBoost is required. Experience with statistical inference, hypothesis testing, and cloud platforms like Azure/AWS, as well as deploying models in production, will be beneficial for this role. Excellent communication and interpersonal skills are necessary to convey complex analytical concepts to diverse stakeholders effectively.,

At Lilly, you are part of a global healthcare leader that is committed to uniting caring with discovery to enhance the lives of people worldwide. With our headquarters in Indianapolis, Indiana, our dedicated team of 39,000 employees collaborates to discover and deliver life-changing medicines, enhance disease understanding and management, and contribute to our communities through philanthropy and volunteerism. Our focus is on making a positive impact on people's lives around the world. As part of our ongoing efforts, we are in the process of developing and internalizing a cutting-edge recommendation engine platform. This platform aims to streamline sales and marketing operations by analyzing diverse data sources, implementing advanced personalization models, and seamlessly integrating with other Lilly operations platforms. The goal is to provide tailored recommendations to our sales and marketing teams at the individual doctor level, enabling informed decision-making and enhancing customer experience. Responsibilities: - Utilize deep learning models to optimize Omnichannel Promotional Sequences for sales teams - Analyze large datasets to identify trends and relevant information for modeling decisions - Translate business problems into statistical problem statements and propose solution approaches - Collaborate with stakeholders to effectively communicate analysis findings - Preference for familiarity with pharmaceutical datasets and industry - Experience in code refactoring, model training, deployment, testing, and monitoring for drift - Optimize model hyperparameters and adapt to new ML techniques for business problem-solving Qualifications: - Bachelor's degree in Computer Science, Statistics, or related field (preferred) - 2-6 years of hands-on experience with data analysis, coding, and result interpretation - Proficiency in coding languages like SQL or Python - Prior experience with ML techniques for recommendation engine models in healthcare sectors - Expertise in Feature Engineering, Selection, and Model Validation on Big Data - Familiarity with cloud technology, particularly AWS, and tools like Tableau and Power BI At Lilly, we are committed to promoting workplace diversity and providing equal opportunities for all individuals, including those with disabilities. If you require accommodation during the application process, please complete the accommodation request form on our website. Join us at Lilly and be part of a team dedicated to making a difference in the lives of people worldwide.,