4 Bayesian Models Jobs

As an Analytics Associate Manager in the Insights and Intelligence vertical at Accenture, you will be responsible for generating insights using the latest Artificial Intelligence (AI) and Analytics techniques to deliver value to clients. Your expertise will be crucial in building world-class solutions, tackling business problems, and overcoming technical challenges using AI Platforms and technologies. It will be essential for you to leverage existing frameworks, standards, and patterns to establish architectural foundation and services needed for scalable AI applications, demonstrating your expertise through active blogging, publishing research papers, and creating awareness in this emerging field. You will be a key member of the Marketing & Customer Analytics team, which focuses on measuring, managing, and analyzing marketing activities to provide actionable insights and recommendations for optimizing ROI and operational efficiency. Your exposure to digital marketing, A/B testing, MVT, Google Analytics/Site Catalyst will be valuable in this role. Additionally, you will play a vital role in the Accenture Operations global Applied Intelligence group, working with machine learning and advanced analytics to drive data-driven decision-making and business transformation. Your responsibilities will include leading a team of data scientists to develop and deploy data science models, refining and enhancing these models based on feedback and evolving business needs. You will analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. We are looking for candidates with extensive experience in leading Data Science and Advanced Analytics delivery teams, strong statistical programming skills in Python, R, SAS, S-plus, MATLAB, STATA, or SPSS, and experience with large data sets and big data tools like Snowflake, AWS, and Spark. Moreover, you should have solid knowledge in areas such as Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling, Multivariate Statistics, Non-parametric Methods, Reliability Models, Markov Models, Stochastic models, Bayesian Models, and experience in domains like CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, and Supply Chain. Your role will involve client engagement, business development, and working in a global collaborative team environment. In summary, as an Analytics Associate Manager at Accenture, you will play a crucial role in leveraging data science and advanced analytics to drive insights and value for clients, while contributing to the growth and success of the organization.,

You are seeking a seasoned Deputy Manager/Group Manager in Advanced Analytics for the Lifesciences/Pharma domain. Your primary responsibility will be to lead a dynamic team focused on assisting clients in Marketing, Sales, and Operations through advanced data analytics. Your proficiency in ML & DL Algorithms, NLP, Generative AI, Omni Channel Analytics, and Python/R/SAS is essential. Your role involves partnering with the Clients Advanced Analytics team to identify, scope, and execute advanced analytics efforts that answer business questions, solve business needs, and add business value. You will maintain a broad understanding of pharmaceutical sales, marketing, and operations to develop analytical solutions in these areas. It is crucial to stay current with statistical/mathematical/informatics modeling methodology and justify the methods selected. You will also lead the team independently to implement & deliver complex project assignments and provide strategic leadership to build new capabilities within the group. Additionally, you will contribute to whitepapers and articles at the BU and organization level, develop and deliver formal presentations to senior clients, and possess strong interpersonal communication, teamwork, leadership, and self-management skills. You should bring an insatiable desire to learn, innovate, and challenge yourself for the benefit of patients. Eligibility criteria include a minimum of 4-10 years of experience in data analytics and 2-4 years of relevant experience in Healthcare/Lifesciences/Pharmaceutical domain. Technical skills required for this role include proficiency in Python or R for statistical and machine learning applications, expertise in various techniques like Regression, Classification Decision Trees, Text Mining, Natural Language Processing, Bayesian Models, and more. You should be able to build & train neural network architectures and have hands-on experience in NLP & NLG. Knowledge in LLMs and Cloud Platforms like Azure, AWS, GCP is essential. Exposure to big data technologies is a plus. Basic qualifications include a B.Tech/Masters in a quantitative discipline such as Applied Mathematics, Computer Science, Bioinformatics, Statistics, Ops Research, or Econometrics. Your role will involve making the impossible possible in the quest to make life better, bringing Analytics to life, and continuously learning to maximize your impact in the field.,

Are you passionate about the intersection of data, technology, and science, and excited by the potential of Real-World Data (RWD) and AI Do you thrive in collaborative environments and aspire to contribute to the discovery of groundbreaking medical insights If so, join the data42 team at Novartis! At Novartis, we reimagine medicine by leveraging state-of-the-art analytics and our extensive internal and external data resources. Our data42 platform grants access to high-quality, multi-modal preclinical and clinical data, along with RWD, creating the optimal environment for developing advanced AI/ML models and generating health insights. Our global team of data scientists and engineers utilizes this platform to uncover novel insights and guide drug development decisions. As an RWD SME / RWE Execution Data Scientist, you will focus on executing innovative methodologies and AI models to mine RWD on the data42 platform. You will be the go-to authority for leveraging diverse RWD modalities patterns crucial to understanding patient populations, biomarkers, and drug targets, accelerating the development of life-changing medicines. Duties and Responsibilities: - Collaborate with R&D stakeholders to co-create and implement innovative, repeatable, scalable, and automated data and technology solutions in line with data42 strategy. - Be a data Subject Matter Expert (SME), understand Real World Data (RWD) of different modalities, vocabularies (LOINC, ICD, HCPCS, etc.), non-traditional RWD (Patient reported outcomes, Wearables and Mobile Health Data) and where and how they can be used, including in conjunction with clinical data, omics data, pre-clinical data, and commercial data. - Contribute to data strategy implementation such as Federated Learning, tokenization, data quality frameworks, regulatory requirements (submission data to HL7 FHIR formats conversion, Sentinel initiative), conversion to common data models and standards (OMOP, FHIR, SEND, etc.), FAIR principles, and integration with enterprise catalog. - Define and execute advanced integrated and scalable analytical approaches and research methodologies (including industry trends) in support of exploratory and regulatory use of AI models for RWD analysis across the Research Development Commercial continuum by facilitating research questions. - Stay current with emerging applications and trends, driving the development of advanced analytic capabilities for data42 across the Real-world evidence generation lifecycle, from ideation to study design and execution. - Demonstrate high agility working across various cross-located and cross-functional associates across business domains (commercial, Development, Biomedical Research) or Therapeutic area divisions for our priority disease areas to execute complex and critical business problems with quantified business impact/ROI. Ideal Candidate Profile: - PhD or MSc. in a quantitative discipline (e.g., but not restricted to Computer Science, Physics, Statistics, Epidemiology) with proven expertise in artificial Intelligence / Machine Learning. - 8+ years of relevant experience in Data Science (or 4+ years post-qualification in case of PhD). - Extensive experience in Statistical and Machine Learning techniques: Regression, Classification, Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining, and Natural Language Processing, LLMs, and multi-modal Generative AI. - Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Optimization techniques including, Dynamic Programming Deep Learning techniques on structured and unstructured data, Recommender Systems. - Proficiency in tools and packages: Python, R(optional), SQL; exposure to dashboard or web-app building using PowerBI, R-Shiny, Flask, open source or proprietary software and packages is an advantage. - Knowledge in data standards e.g. OHDSI OMOP, and other data standards, FHIR HL7 for regulatory, and best practices. - Good to have: Foundry, big data programming, working knowledge of executing data science on AWS, DataBricks, or SnowFlake. - Strong in Matrix collaboration environments with good communication and collaboration skills with country/ regional/ global stakeholders in an individual contributor capacity. Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting, and inspiring each other. Combining to achieve breakthroughs that change patients" lives. Ready to create a brighter future together Join our Novartis Network: Not the right Novartis role for you Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up. Benefits and Rewards: Read our handbook to learn about all the ways we'll help you thrive personally and professionally.,

Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills