12 Feature Selection Jobs

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS Consulting digital engineering is seeking an experienced Azure Cloud and Python Developer for ML to join our Emerging Technologies team in DET, GDS. This role presents an exciting opportunity to contribute to innovative projects and be a key player in shaping our technological advancements. We are seeking an experienced Azure Cloud and Python Developer with 6-8 years of hands-on experience in machine learning (ML) development. This role involves developing and deploying ML models on the Azure cloud platform, designing efficient data pipelines, and collaborating with data scientists and stakeholders to deliver technical solutions. **Your Key Responsibilities** - Develop and deploy machine learning models on Azure cloud platform using Python programming language, ensuring scalability and efficiency. - Design and implement scalable and efficient data pipelines for model training and inference, optimizing data processing workflows. - Collaborate closely with data scientists and business stakeholders to understand requirements, translate them into technical solutions, and deliver high-quality ML solutions. - Implement best practices for ML development, including version control using tools like Git, testing methodologies, and documentation to ensure reproducibility and maintainability. - Design and optimize ML algorithms and data structures for performance and accuracy, leveraging Azure cloud services and Python libraries such as TensorFlow, PyTorch, or scikit-learn. - Monitor and evaluate model performance, conduct experiments, and iterate on models to improve predictive accuracy and business outcomes. - Work on feature engineering, data preprocessing, and feature selection techniques to enhance model performance and interpretability. - Collaborate with DevOps teams to deploy ML models into production environments, ensuring seamless integration and continuous monitoring. - Stay updated with the latest advancements in ML, Azure cloud services, and Python programming, and apply them to enhance ML capabilities and efficiency. - Provide technical guidance and mentorship to junior developers and data scientists, fostering a culture of continuous learning and innovation. **Skills And Attributes** **Soft Skills** - Bachelor's or master's degree in computer science, data science, or a related field, with a strong foundation in ML algorithms, statistics, and programming concepts. - Minimum 6-8 years of hands-on experience in developing and deploying ML models on Azure cloud platform using Python programming language. - Expertise in designing and implementing scalable data pipelines for ML model training and inference, utilizing Azure Data Factory, Azure Databricks, or similar tools. - Proficiency in Python programming language, including libraries such as TensorFlow, PyTorch, scikit-learn, pandas, and NumPy for ML model development and data manipulation. - Strong understanding of ML model evaluation metrics, feature engineering techniques, and data preprocessing methods for structured and unstructured data. - Experience with cloud-native technologies and services, including Azure Machine Learning, Azure Kubernetes Service (AKS), Azure Functions, and Azure Storage. - Familiarity with DevOps practices, CI/CD pipelines, and containerization tools like Docker for ML model deployment and automation. - Excellent problem-solving skills, analytical thinking, and attention to detail, with the ability to troubleshoot and debug complex ML algorithms and systems. - Effective communication skills, both verbal and written, with the ability to explain technical concepts to non-technical stakeholders and collaborate in cross-functional teams. - Proactive and self-motivated attitude, with a passion for learning new technologies and staying updated with industry trends in ML, cloud computing, and software development. - Strong organizational skills and the ability to manage multiple projects, prioritize tasks, and deliver results within project timelines and specifications. - Business acumen and understanding of the impact of ML solutions on business operations and decision-making processes, with a focus on delivering value and driving business outcomes. - Collaboration and teamwork skills, with the ability to work effectively in a global, diverse, and distributed team environment, fostering a culture of innovation and continuous improvement. To qualify for the role, you must have a bachelor's or master's degree in computer science, data science, or a related field, along with a minimum of 6-8 years of experience in ML development and Azure cloud platform expertise. Strong communication skills and consulting experience are highly desirable for this position. **Ideally, you'll also have** - Analytical ability to manage complex ML projects and prioritize tasks efficiently. - Experience operating independently or with minimal supervision, demonstrating strong problem-solving skills. - Familiarity with other cloud platforms and technologies such as AWS, Google Cloud Platform (GCP), or Kubernetes is a plus. **What Working At EY Offers** At EY, we're dedicated to helping our clients, from startups to Fortune 500 companies, and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: - Support, coaching, and feedback from engaging colleagues - Opportunities to develop new skills and progress your career - Freedom and flexibility to handle your role in a way that's right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people, and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Working across assurance, consulting, law, strategy, tax, and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

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. Your Role 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 Productionlization Your Profile 5-14 years of 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. Proven experience in enhancing model accuracy through engineering techniques, such as feature engineering, feature selection, and data augmentation. Strong expertise in deploying machine learning models to production systems. What you will love about working here We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain 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.

You will be responsible for applying Natural Language Processing (NLP) AI techniques, conducting machine learning, and developing high-quality prediction systems for data classification. Your main tasks will include presenting information through data visualization techniques, as well as collecting, preprocessing, and harmonizing data. As a part of your role, you will develop applications in machine learning and artificial intelligence, while selecting features, building, and optimizing classifiers using machine learning techniques. Understanding business objectives and creating models to support them, along with relevant metrics to monitor progress, will be crucial. You will need to manage available resources efficiently, such as hardware, data, and personnel, to ensure project deadlines are met. Your responsibilities will also involve analyzing various ML algorithms to identify the most suitable ones for solving a specific problem and ranking them based on success probability. Exploring and visualizing data to comprehend it better, detecting variations in data distribution that could impact model performance in real-world deployment, and verifying data quality through cleaning processes will be essential. You will supervise the data acquisition process if additional data is required, search for relevant datasets online for training purposes, define validation strategies, and determine pre-processing or feature engineering on datasets. Furthermore, you will be involved in defining data augmentation pipelines, training models, tuning hyperparameters, analyzing model errors, and developing strategies to address them. Deployment of models to production environments will also be a key aspect of your role. As a desired candidate, you should possess a strong understanding of machine learning (ML) and deep learning (DL) algorithms, as well as an architectural comprehension of CNN and RNN algorithms. Experience with NLP data models and libraries, entity extraction using NLP, and proficiency in tools like TensorFlow, scikit-learn, and spaCy is required. Additionally, familiarity with transfer learning, scripting and programming skills in Python and Streamlit, common data science toolkits such as NumPy and Fast.AI, and various machine learning techniques and algorithms like k-NN, Naive Bayes, and SVM is essential. Proficiency in query languages, applied statistics skills, data wrangling, data exploration, as well as tools like Tableau and DataPrep will be advantageous. The ideal candidate will be an immediate joiner with no restrictions on salary for the right individual.,

Are you passionate about building intelligent systems that make a real-world impact Do you enjoy working in a fast-paced and dynamic start-up environment If so, we are looking for a talented AI Developer to join our team! We are a data and AI consultancy start-up with a global client base, headquartered in London UK, and we are looking for someone to join us full time on-site in our vibrant office in Gurugram. About Uptitude Uptitude is a forward-thinking consultancy that specialises in providing exceptional AI, data, and business intelligence solutions to clients worldwide. Our team is passionate about delivering data-driven transformation and intelligent automation, enabling our clients to make smarter decisions and achieve remarkable results. We embrace a vibrant and inclusive culture where innovation, excellence, and collaboration thrive. As an AI Developer at Uptitude, you will be responsible for designing, developing, and deploying AI models and solutions across a wide range of use cases. You will collaborate closely with data engineers, analysts, and business teams to ensure models are well-integrated, explainable, and scalable. We are looking for a candidate who is not only technically skilled but also creative, curious, and excited about pushing the boundaries of AI in real-world business environments. Requirements - 3 years of hands-on experience in developing AI/ML models in production or research settings. - Proficiency in Python and libraries such as scikit-learn, Pandas, TensorFlow, PyTorch. - Experience working with structured and unstructured data. - Familiarity with model lifecycle management, MLOps, and version control (MLflow, DVC). - Ability to communicate technical ideas to cross-functional teams. - Experience with data cleaning, EDA, and feature selection. - Creativity in applying AI to real-world business problems. Awareness of ISO:27001, ISO:42001 and data governance best practices is a plus. Role based in Gurugram, India. Head office in London, UK. Company Values At Uptitude, we embrace a set of core values that guide our work and define our culture: - Be Awesome: Strive for excellence and keep levelling up. - Step Up: Take ownership and go beyond the expected. - Make a Difference: Innovate with impact. - Have Fun: Celebrate wins and build meaningful connections. Benefits Uptitude values its employees and offers a competitive benefits package, including: - Competitive salary based on experience and qualifications. - Private health insurance. - Offsite trips for team building and knowledge sharing. - Quarterly outings to celebrate milestones. - Corporate English lessons with a UK-based instructor. If you're ready to develop cutting-edge AI solutions and work on meaningful challenges with a global impact we'd love to hear from you.,

Develop strategies/solutions to solve problems in logical yet creative ways, leveraging state-of-the-art machine learning, deep learning and GEN AI techniques. Technically lead a team of data scientists to produce project deliverables on time and with high quality. Identify and address client needs in different domains, by analyzing large and complex data sets, processing, cleansing, and verifying the integrity of data, and performing exploratory data analysis (EDA) using state-of-the-art methods. Select features, build and optimize classifiers/regressors, etc. using machine learning and deep learning techniques. Enhance data collection procedures to include information that is relevant for building analytical systems, and ensure data quality and accuracy. Perform ad-hoc analysis and present results in a clear manner to both technical and non-technical stakeholders. Create custom reports and presentations with strong data visualization and storytelling skills to effectively communicate analytical conclusions to senior officials in a company and other stakeholders. Expertise in data mining, EDA, feature selection, model building, and optimization using machine learning and deep learning techniques. Strong programming skills in Python. Excellent communication and interpersonal skills, with the ability to present complex analytical concepts to both technical and non-technical stakeholders. Primary Skills : - Excellent understanding and hand-on experience of data-science and machine learning techniques & algorithms for supervised & unsupervised problems, NLP and computer vision and GEN AI. Good applied statistics skills, such as distributions, statistical inference & testing, etc. - Excellent understanding and hand-on experience on building Deep-learning models for text & image analytics (such as ANNs, CNNs, LSTM, Transfer Learning, Encoder and decoder, etc). - Proficient in coding in common data science language & tools such as R, Python. - Experience with common data science toolkits, such as NumPy, Pandas, Matplotlib, StatsModel, Scikitlearn, SciPy, NLTK, Spacy, OpenCV etc. - Experience with common data science frameworks such as Tensorflow, Keras, PyTorch, XGBoost,etc. - Exposure or knowledge in cloud (Azure/AWS). - Experience on deployment of model in production. Show more Show less

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

The role of a member in the New Analytics Team based in Hyderabad involves understanding business processes and data to model requirements for creating analytics solutions. You will be responsible for building predictive models and recommendation engines using cutting-edge machine learning techniques to enhance the efficiency and effectiveness of business processes. Your tasks will include churning and analyzing data to identify actionable insights and patterns for business use. Additionally, you will assist the Function Head in data preparation and modeling tasks as required. Collaboration with both business and IT teams is essential for understanding and collecting data. Your responsibilities will also include collecting, collating, cleaning, processing, and transforming large volumes of primarily tabular data comprising numerical, categorical, and some textual information. Applying data preparation techniques such as data filtering, joining, cleaning, missing value imputation, feature extraction, feature engineering, feature selection, dimensionality reduction, feature scaling, and variable transformation will be a part of your routine tasks. You will be expected to apply basic algorithms like linear regression, logistic regression, ANOVA, KNN, various clustering methods, SVM, Naive Bayes, decision trees, principal components, and association rule mining. Additionally, ensemble modeling algorithms like bagging (Random Forest), boosting (GBM, LGBM, XGBoost, CatBoost), time-series modeling, and other state-of-the-art algorithms will also be utilized as required. Your role will involve employing modeling concepts such as hyperparameter optimization, feature selection, stacking, blending, K-fold cross-validation, bias and variance, and combating overfitting. Building predictive models using state-of-the-art machine learning techniques for regression, classification, clustering, recommendation engines, etc., will be a key part of your responsibilities. Furthermore, you will analyze business data to uncover hidden patterns and insights, identify explanatory causes, and make strategic recommendations based on your findings. To excel in this role, you should hold a BE/B. Tech degree in any stream and possess strong expertise in Python libraries like Pandas and Scikit Learn. Proficiency in coding according to the outlined requirements is essential. Experience with Python editors such as PyCharm and/or Jupyter Notebooks is a must, along with the ability to organize code into modules, functions, and/or objects. Knowledge of using ChatGPT for machine learning will be advantageous, while familiarity with basic SQL for querying and Excel for data analysis is necessary. Understanding basics of statistics, including distributions, hypothesis testing, and sampling techniques, is a prerequisite. Experience with Kaggle and familiarity with R are desirable. Ideal candidates will have a minimum of 4 years of experience solving business problems through data analytics, data science, and modeling, with at least 2 years of full-time experience as a data scientist. They should have worked on at least 3 projects involving ML model building that were utilized in production by businesses or other clients. Your primary responsibilities will include spending 35% of your time on data preparation for modeling, 35% on building ML/AI models for various business requirements, 20% on performing custom analytics to provide actionable insights to the business, and 10% on assisting the Function Head in data preparation and modeling tasks as needed. Candidates without familiarity with deep learning algorithms, image processing and classification, and text modeling using NLP techniques will not be considered for selection. For applying to this position, please email your application to careers@isb.edu.,

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.,

Qualification Masters related to Bioinformatics and Computational Biology Role & responsibilities - Combine and analyze multi-omics datasets to find common biological signals and actionable targets. - Classify disease and immune subtypes from both bulk and single-cell data using supervised and unsupervised machine learning methods. - Organize public datasets, evaluate analytical tools, and standardize workflows for clarity and reuse. - Conduct quality control, normalization, subtype and signature predictions across various sequencing platforms. - Create and maintain complete analysis pipelines for new technologies such as spatial transcriptomics - Search large consortia or databases for comparative studies and hypothesis generation. - Optimize resource use and job scheduling on Linux or HPC clusters; maintain version control and documentation. Preferred candidate profile - Programming & Scripting: R, Python, UNIX shell - Statistics & ML: Feature selection, clustering, predictive modeling, dimensionality reduction, survival analysis - Bulk & Single-Cell Analytics: RNA-seq, WES/WGS, methylation, proteomics, RPPA, scRNA-seq - Workflow & Reproducibility: Workflow managers, such as Nextflow or Snakemake, containers, Git - Data Resources: Major public repositories like TCGA and GEO, and internal cohort data management

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.,