eClinical Solutions’ Post

There's a common misconception that a biomedical degree and experience are a must for becoming a data scientist in healthcare. Let me categorize the different types of healthcare data scientist roles: 1️⃣ The Applied Scientist: These individuals work in research settings. Such positions often require a biomedicine degree and sometimes, relevant experience. Examples include bioinformaticians, biostatisticians, and pharma data scientists. 2️⃣ The Research Engineer: These roles demand technical expertise in data science areas like NLP, computer vision, signals processing, etc. for developing healthcare AI applications. My current role aligns with this category, as I specialize in developing LLM-based applications. 3️⃣ The Product Data Scientist: These professionals focus on enhancing product user experience, revenue, marketing, and distribution through data-driven insights. These positions call for knowledge and experience in statistics and some ML. Good communication skills are required for these types of roles. For research and product data scientist roles, healthcare-specific experience is an advantage but not essential. Fortunately, many opportunities today fall into the second and third categories. These present ideal pathways for those aspiring to enter the rewarding field of healthcare data science. #datascientist #jobs #healthcare #artificialintelligence

𝗪𝗵𝗮𝘁 𝘄𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗱... 𝗳𝗿𝗼𝗺 𝗿𝗲𝗰𝗿𝘂𝗶𝘁𝗶𝗻𝗴 𝗮 𝗱𝗿𝘂𝗴 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 𝗶𝗻 𝟮 𝘄𝗲𝗲𝗸𝘀 Data Scientists are enabling the future of AI and ML powered drug discovery and design, utilising their computational biology and data analysis domain expertise. It's no surprise their skills are in high demand in the world of biotech and drug discovery. Here are three things we learned from helping a VP Data Science at a Bay Area AI-drug discovery biotech recruit a Sr Data Scientist in 2 weeks: 💊𝗙𝗹𝗲𝘅𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗼𝗻 𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: despite the HQ been in the Bay, the VP Data Science was pro-remote working, meaning our talent pool increased tenfold, and we were able to conduct streamlined virtual interviews in week 1, and an offer accepted in week 2. It's no surprise their existing team had an impressive 𝘳𝘦𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘳𝘢𝘵𝘦 𝘰𝘧 >95%. 💊𝗕𝗶𝗼𝗺𝗮𝗿𝗸𝗲𝗿 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: with the surge of biomarker discovery research, it was reassuring to see lots of recent data scientists majoring in deep machine learning with biomarker ID or single cell transcriptomic approaches. 💊𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗺𝗲𝗲𝘁𝘀 𝘀𝘆𝗻𝗲𝗿𝗴𝗶𝘀𝘁𝗶𝗰 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 𝗽𝗵𝗮𝗿𝗺𝗮𝗰𝗼𝗹𝗼𝗴𝘆: a lot of prospects were showing a keen interest in the emerging field of multi-drug target research which utilizes deep learning computational algorithms to overcome the analysis of very big biological data sets. Although this particular client had no existing pipeline applications here, it signalled pro-activity and awareness to emerging trends in the field, which the hiring team loved. AI and ML technology will continue to be hot topics across the biotech field for years to come, and the demand for talent isn't slowing down. Get in touch if you're seeking guidance on how to identify and hire the right data scientists for your drug discovery/pipeline goals: E: Adam.butler@mason-harding.com #datascience #machinelearning #drugdiscovery #masonharding

We're making space for one more at the table! Infinitus is #hiring a senior data scientist to support our LLM efforts and #AI innovation in San Franscisco. To learn more, send a message to Ritu Rastogi, or apply via the link in the comments. #aicareers #datascience #healthcareai

DVA is not associated with this job posting Staff Data Scientist at Correlation One https://lnkd.in/gFGbuM65 A Day In the Life: Architect and build scalable machine learning solutions and AI applications Design and implement reliable, reusable frameworks and abstractions to standardize AI model development. Engage in hands-on development, from model prototyping to deploying scalable AI systems. Lead efforts to ensure that AI models and data practices uphold ethical standards, including fairness, transparency, and accountability. Work closely with product managers and business stakeholders to translate business challenges into data-driven projects that deliver measurable outcomes. Mentor junior data scientists and foster a culture of technical excellence. Stay updated and educate the team on the latest trends in AI and machine learning technologies. #employeeexperience #people #culture #hiring #talent #skills #passion #leadership #hr #humanresources #team #strategy #hrstrategy #business #team #careers #employment #jobs #hiring #job #jobsearch #recruitment #career #work #careers #recruiting #nowhiring #resume #jobhunt #business #jobseekers #jobopening #jobseeker #hiringnow #interview #jobsearching #vacancy #cfbr #education #jobinterview #jobopportunity #employmentopportunities

👩⚕️🔬 Bridging Biomedical Engineering and Data Analytics: A World of Possibilities 🔬👨⚕️ Hey LinkedIn community! I’ve been reflecting on the exciting intersection of biomedical engineering and data analytics, and I’m thrilled to share some insights on the boundless opportunities this combination offers. As a biomedical engineer stepping into the world of data, I’ve realized how powerful this blend can be. Here’s why: 🌟 Transforming Healthcare with Data 🌟 1. Healthcare Data Analysis: By diving into electronic health records (EHRs), we can enhance patient care and streamline hospital operations. Predictive analytics can foresee patient outcomes, making healthcare proactive rather than reactive. 2. Medical Imaging: Imagine using machine learning to analyze MRI and CT scans. We’re talking about more accurate diagnostics and better treatment planning! 3. Genomics and Bioinformatics: Genomic data analysis is like unlocking the secrets of our DNA. It helps in personalized medicine, ensuring treatments are tailored to individual genetic profiles. 4. Wearable Health Tech: From fitness trackers to smartwatches, analyzing data from wearables can revolutionize real-time health monitoring and remote patient care. 5. Drug Development: Analyzing clinical trial data ensures new drugs are safe and effective. It’s a critical step in bringing innovative treatments to market. 🛠️ Essential Skills and Tools 🛠️ To thrive in this space, here are some skills and tools that have been game-changers for me: - Programming: Python, R, and MATLAB. - Data Analysis: Pandas, NumPy, SciPy, and SQL. - Machine Learning: Scikit-Learn, TensorFlow, Keras, and PyTorch. - Visualization: Matplotlib, Seaborn, ggplot2, and Plotly. - Statistical Analysis: A solid grasp of statistical methods. 🚀 Career Paths 🚀 The fusion of these fields opens up diverse career paths: - Healthcare Data Scientist - Biomedical Data Analyst - Clinical Data Manager - Health Informatics Specialist - Bioinformatics Analyst - Medical Imaging Analyst #BiomedicalEngineering #DataAnalytics #HealthcareInnovation #MachineLearning #Genomics #HealthTech

I think starting a small project can help us find our passion and career path in data-driven healthcare. Just diving is not the key, before diving into a career in data mining for AI-driven healthcare projects, understanding the various career paths and opportunities can be tremendously beneficial. It allows individuals to gain insights into the diverse roles available in this field, such as data scientists, machine learning engineers, or healthcare analysts.    Exploring these options helps identify the specific skill sets, educational background, and experience required for each role, aiding in career planning and preparation. Having this understanding of career paths and opportunities equips aspiring professionals with a solid foundation and direction in pursuing a successful and fulfilling career in data mining within the AI-driven healthcare. #healthcare #artificialintelligence #data #project

#hiring *Statistician (f/m/x)*, Hannover, *Germany*, fulltime #opentowork #jobs #jobseekers #careers #Hannoverjobs #Niedersachsenjobs #ScienceTechnology *Apply*: https://lnkd.in/gnFqaVk8 Passion for Innovation. Compassion for Patients. With over 120 years of experience and more than 17,000 employees in over 20 countries, Daiichi Sankyo is dedicated to discovering, developing, and delivering new standards of care that enrich the quality of life around the world. In Europe, we focus on two areas: The goal of our Specialty Business is to protect people from cardiovascular disease, the leading cause of death in Europe, and help patients who suffer from it to enjoy every precious moment of life. In Oncology, we strive to become a global pharma innovator with competitive advantage, creating novel therapies for people with cancer. Our European headquarters are in Munich, Germany, and we have affiliates in 13 European countries and Canada. For our European Headquarter in Munich or other affiliates in Europe we are looking for a Principal Statistical Programmer RWE EU (m/f/x) The ideal candidate for this position will provide statistical/data science programming as well as technical support for Daiichi Sankyo's EU RWE projects/initiatives by close collaboration with EU or US based RWE biostatistician and other collaborators. This role will deliver the values through secondary data such as EMR or claims data analysis. Roles & responsibilities: EU RWE Statistical analysis support: Provide programming support for EU RWE project or study to deliver the TLFs on time and support ad-hoc requests. Statistical macro: Develop necessary programming macros or tools to effectively support all programming needs. Responsibilities include developing the macros or tools e.g., interactive web based tools such as R Shiny to facilitate programing efficiency, bring an innovative ideas/solution to the projects, supporting the maintenance of pre-existing macros. Evaluate, assess, and enhance DSI computing environment system: Assess DSI new computing environment system for programming and analysis efficiency, identify system bug/issue and lead the activity to enhance the system, develop system training materials and work as the SME to support implementation, evaluate, request and approve system upgrades, and propose/develop system utilities, provide input to build a strong RWD environment, RWE computing environment, promote innovative solutions, operational excellence and develop efficient processes and standards for RWE. Advanced analytics: Demonstrate high level proficiency for Artificial Intelligence (AI) and Machine Learning (ML) technology, building predictive models, and application of External Control Arm, align with future roadmap, network with other business area/analytics group to promote the advanced analytics or methodologies. Successful candidates will be able to meet the qualifications below with or without

DVA is not associated with this job posting Senior Data Scientist United States, Remote https://lnkd.in/g_3af_K7 Purpose of the Job Sr Data Scientist leads and drives strategic AI solutions, leveraging advanced data science expertise and innovative problem-solving skills. As a Senior Data Scientist, the role involves designing complex AI solutions aligned with business objectives, utilizing a deep understanding of cutting-edge algorithms and methodologies. This position focuses on continuous learning and adaptation to emerging technologies, ensuring the highest level of technical mastery. Additionally, the role emphasizes collaboration, mentorship, and thought leadership to contribute to the organization's growth and maintain a standard of excellence in AI solution design and deployment. Responsibilities & Accountabilities AI Solution Design and Development: Lead the design and development of AI solutions, identifying complex business problems and developing high-level architectures with minimal guidance. Evaluate various algorithms and data sets to determine the most effective solutions for given business problems, ensuring optimal model performance. Handle AI solution requirement gathering, design, and development process management to meet business objectives and stakeholder needs. Effectively communicate insights, recommendations, and AI solution progress to stakeholders, ensuring alignment with business goals. Develop customized models tailored to specific business problems using advanced machine learning algorithms and handling complex and unstructured data sets. #employeeexperience #people #culture #hiring #talent #skills #passion #leadership #hr #humanresources #team #strategy #hrstrategy #business #team #careers #employment #jobs #hiring #job #jobsearch #recruitment #career #work #careers #recruiting #nowhiring #resume #jobhunt #business #jobseekers #jobopening #jobseeker #hiringnow #interview #jobsearching #vacancy #cfbr #education #jobinterview #jobopportunity #employmentopportunities