Job Description

Summary To provide data science and quantitative analytical support for PS&PV by ensuring timely delivery of high-quality reports to meet regulatory requirements, enable medical safety analysis and monitor safety profile of Novartis products. Build capabilities to leverage the Science of data to enhance safety surveillance, case management and delivery of management metrics. These tasks are to be performed independently. Responsible for independently managing small to medium Projects.Major Accountabilities:xe2x96xaa Engineer key analytical insights into simple, intuitive, and well-designed tools and ser vices tailored for each role and process in areas such as:aggregate analysis and reports including PSUR, DSUR, PQR, APR and audit/inspec- tion related outputsPV leaning analyticsbudget forecastingresource allocation and vendor management supportpatient focused protocol design and reported outcome.risk-based operational monitoring of country operationsdetecting data anomalies, outliers and procedural errorssignal detectiontrack the businessxe2x80x99s performance against data analysis model and monitor trends in key business KPIs, providing valuable insights to relevant departments for overall business performance improvement.Provide solutions for a variety of business applications including but not limited to:Customer Segmentation & Targeting, Event Prediction, Propensity Modelling, Churn Modelling, Customer Lifetime Value Estimation, Forecasting, Recommender Systems, Modelling Response, OptimizationCollaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems, drive operational efficiencies, and deliver successfully on high visibility strategic initiatives.Interact with domain experts to understand the data and the business challenges and design solutions to the challenges using data.Ability to translate business questions into analytical problems and build solutions using visualization techniques, machine learning, statistical modeling.Independently manage small to medium projects.Ability to provide understandable and actionable business intelligence for key stakeholders.Research and develop new algorithms, methods, statistical models and business models and providing insight into structured and unstructured data.Working with the internal process experts and key stakeholders in providing analysis and interpretation of safety/PV data.Is responsible in creation of new data sciences capabilities for the business by envisioning and executing strategies that will influence improvement of the businessxe2x80x99s performance by enabling informed decision making.Collaborate with partners in IT and Development functions to improve the availability of data (near-real time data flows) and data quality as required for high quality, innovative, analytical/ technical solutions.Bring in efficiency with innovative solutions; effective usage of new technologies and con- cepts; developing new analysis opportunities by integrating existing and new data sources.Continuously monitor external environment to ensure that the organisation can leverage key developments in data science and AI.Lead the design and oversees the development of predictive and data-driven solutions (for ex: SafetyReporting tool) and services to ensure drug, device, trial and patient level benefit/risk information is available proactively for safety analysis, signal detection and risk management.Manage timely delivery of high quality PV& Medical safety listing, analysis and data and ensure compliance with health authority regulations.Supports and represents Dats Science team in regulatory inspections/audits, as and when required.Should mentor and coach data science leads, by guiding them through the execution of their duties, and encouraging their professional growth in preparation for their occupation of his position in future.Act as deputy of Sr. Manager Data Science and AI/Head Data Science/Head Data Analytics as and when needed.Minimum requirements :Masters/Bachelorxe2x80x99s Degree in Data Science, Statistics, Math- ematics, Operations Research, Engineering (Biotech, Com- puter Science, Information Technology), Pharmaceutical, Life Science or similar field. MBA/PhD from reputed institutes can also apply.10-15 years of experience in Data Science related fields with specific experience of producing Key Performance Indicators or similar monthly reports for Senior Management and build- ing statistical models for addressing business issues1-3 years of Pharma, CRO, Life Science experience would be preferred.Hands on technical expertise in at least 1 of : Machine Learning, Deep Learning, Text Mining and Natural Language Processing, Time Series, Image processing, Neural Networks.Ability to work independently to be able to design, develope code and manage algorithms / Machine Learning models in Python/R/JavaAdvance level skills in Python/ R is a must, and working knowledge in SQL - ability to write and understand queries and extract complex datasets and produce reports from Databases (including Oracle, SAS, non-relational databases)Pharmacovigilance/Clinical operations domain expertice.Ability to translate technical concepts for non-technical users in the areas of clinical databases (both internal and external).Extensive experience in working with large-scale datasets (in big data architecture, data lake, data mart, data warehouse) and be able to preprocess the data as per the requirement.Ability to work in teams, manage and coordinate projects, under pressure, demonstrating initiative and flexibility through effective and innovative technical ability.Interpersonal and communication skills, and ability to operate effectively in a matrix environmentAttention to detail, quality, time management and customer focusJoin our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here:Skills Desired Apache Hadoop, Applied Mathematics, Big Data, Curiosity, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Proteomics, Python (Programming Language), R (Programming Language), Statistical Modeling

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