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There’s a room to think big and be courageous. In fact, it’s the norm. Be a part of our Data Science Organization. I’m #hiring. Know anyone who might be interested? #pfizer #newjob #newchallenge #pfizercollegue #excellence #equity #pfizerproud #jointheteam #hiring  #thoughtpartnershealthcare   https://lnkd.in/euKtmAEf

Unlocking the Potential of Data Science Data Science is more than a buzzword; it is a dynamic field that is changing the way we think about business, technology, and decision-making. Here are some of the great advantages it provides: 1. Informed Decision-Making: Data Science provides significant insights to firms, enabling informed and strategic decision-making. Say goodbye to uncertainty! 2. It improves efficiency by smoothing processes, automating regular chores, and increasing productivity. Time and resources are better utilized. 3. individualized Experiences: Data Science assists in creating individualized experiences for customers, from product recommendations to bespoke marketing strategies. 4. Predictive Analytics: It is now feasible to forecast future patterns and results, allowing organizations to prepare and adjust proactively. 5. Innovative Products: Data Science drives innovation, resulting in the development of cutting-edge products and services that meet changing client demands. 6. Cost Reduction: Companies can dramatically reduce expenses and increase profitability by finding inefficiencies and streamlining procedures. 7. Healthcare Advances: Data-driven insights in healthcare boost patient care, medication research, and public health activities. 8. Environmental Impact: Data Science, through predictive mode modelling analysis, plays a critical role in monitoring and managing environmental hazards. 9. Career Opportunities: Data scientists are in high demand. It's a field with numerous career options and prospects for advancement. The possibilities in a data-driven world are endless. Whether you're an aspiring data scientist, a company executive, or simply someone interested in the impact of data, getting involved in the realm of data science can have revolutionary effects. Let's keep harnessing data's potential for a brighter, more informed future! #DataScience #Innovation #DataAnalytics 

Unleashing Data Science: Transforming Industries In today's data-driven world, Data Science is the catalyst for innovation across industries. This interdisciplinary field extracts insights from data, empowering businesses to make informed decisions and gain a competitive edge. Data Science Essentials: It involves collecting, cleaning, and analyzing data using advanced algorithms and statistical techniques. Industry Impact: From finance to healthcare and retail, Data Science revolutionizes practices, enhancing fraud detection, personalized healthcare, and customer experiences. Role of Data Scientists: They bridge the gap between data and decision-making, employing technical skills and domain expertise to drive organizational growth. Critical Skills: Proficiency in programming, statistical analysis, and communication are essential for success in Data Science. Future Outlook: With increasing data volumes and technological advancements, the demand for Data Scientists will continue to rise, shaping a data-centric future. Embracing Data Science is essential for businesses and professionals seeking to thrive in the digital age, unlocking endless possibilities for innovation and growth. #Datascience

Need a data scientist that can predict the future..or at least the future behavior of your customers? I know a guy. After extensive world travels, my colleague Vu Pham is back home in Atlanta and ready to take on new clients. With over 20 years of working with data, Vu has an incredible breadth and depth of expertise with digital marketing agencies as well as companies spanning the retail, automotive, travel, and marketing verticals. Vu's specialties in data science revolve around: - Using historical customer data to predict future customer behavior. - Segmenting customers based on historical and predicted behavior. - Developing predictive/optimization models to forecast future performance, both baseline and what-if scenarios. Vu handles all of the legwork required to get clients to the point where those analyses can be performed: - Strategy around choosing the right key performance indicators and tracking the right metrics. - Engineering the data schemas/warehouses required to house the data. - Setting up the processes to collect/transform/cleanse the data. - Visualizing the data and setting up automated reporting. Please reach out if you'd like to explore partnering with Vu! #datascientist #data #consumerbehavior

We have yet to see effective integration between business management and data science teams at our clients. This is nothing new in the era of AI. Our chairman observes that the gap between management and IT professionals has persisted throughout his four decade career. Why? Data scientists know next to nothing about the business prerogatives. They think in terms of models and algorithms and have no practical market experience. They have little understanding of priorities or which solutions make sense. This relegates the data science teams to deal with lower value-added solutions. Business management, on the other hand, knows next to nothing about data science and the use of robust mathematical models (such as LLMs) in management. This makes it close to impossible to give effective guidance to the data scientists. We looked at the profile of senior management at the 50 largest U.S. companies and only 12% of 860 executives have a quantitative education. Because of these two observations, there is a chasm between the two groups. Tellusant's role is to bridge the gap. We have decades of experience in the practical management topics within strategy development. We understand categories and countries better than any company on the planet. This allows us to see patterns where others see chaos. We 1) consult to companies on the best path into the the future; and 2) we implement our findings in robust management-oriented products for use by management. Thus, we serve as a bridge between business management and data science on the topics we have expertise in (e.g., strategy, parts of marketing, M&A due diligence, parts of revenue management). We prefer not to work with the corporate data science teams on the value-added parts because they bring little value, and we view them mainly as a resource for building connectors (APIs etc.) into the corporate systems. Having worked on the ground in 82 countries, for 11 of the 20 largest consumer goods companies, on over 300 projects, as well having deep mathematical and data science roots, Tellusant has a unique position. In VRIO terms: • Valuable: What we know is of immense value to corporations • Rare: The understanding of both global and local markets is not found elsewhere • Inimitable: It will take a Herculean effort to imitate what we are good at • Organized: What we have does not only reside in our heads. It is well organized in our routines —  —  — [2023-11-02] #strategy #management #ceo #datascience

📢 Hiring ! mRNA Data Governance Manager #datagovernance #mrna What if you could participate in building 2 of the most exciting topics these days : mRNA AND Data Strategy ? At Sanofi, we believe that Data Analytics and Artificial intelligence (#AI) can transform how we discover, develop, and deliver vaccines and therapies. To do so, there is a need to align scientific, operational and data practices, establishing a common data continuum across teams (Research & Biomarkers, Process Development & Industrialization, Analytical Sciences, Clinical, Manufacturing, …) and sites. And there is probably no better place than our Center of Excellence (CoE) in Waltham, Massachusetts to accelerate innovation in the mRNA data space. So ... Ready to join us ? Check out our job offer and apply here 👇 https://lnkd.in/eBFNmuXi #hiring #sanofi #datastrategies Voir la traduction

Open Position Announcement Sr Specialist Digital Innovation Responsibilities: We are looking for a Data Scientist who will support a custom Product Finder application with insights gained from analyzing company data. The ideal candidate is adept at using large external and internal data sets to identify similarities, differences between products and using models to recommend the courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams in a global setting. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to data sets. Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes. Develop company A/B testing framework and test model quality. Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Required Knowledge/Skills Abilities Strong experience with programming languages such as R, Python, and SQL. Ability to manipulate data and draw insights from large datasets. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries specifically designed for working with LLMs, RAG, and LMMs. Profound knowledge and hands-on experience with Large Language Models (LLMs), including but not limited to models like GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), and their derivatives. Understanding of the underlying mechanisms, strengths, limitations, and ethical considerations of LLMs. Demonstrated experience with RAG techniques and their applications. Ability to leverage RAG for enhancing the performance of language models by combining the power of retrieval and generative capabilities to provide more accurate, contextually relevant, and information-rich responses. Solid understanding and practical application of LMMs in analyzing data that have multiple levels of correlation or non-constant variability. Experience in applying LMMs to complex datasets to account for both fixed

What are Colgate-Palmolives' #AI ambitions?! 🚀 Based on a recent Data Scientist job ad by Colgate-Palmolive, it's evident that the global powerhouse in #Food & #Beverage is capitalizing on artificial intelligence (AI) and machine learning to achieve its business objectives. 🌐 Colgate-Palmolive aims to unlock the power of data by developing impactful data products, implementing cutting-edge machine learning models, and optimizing their data science architecture for more efficient analysis. Their focus on advanced analytics in the Global Supply Chain underscores their commitment to generating valuable insights and making informed business decisions. 💡 By leveraging AI and machine learning, Colgate-Palmolive is poised to enhance its operations and maintain a leading edge in the industry. 📊 To learn more about how AI can revolutionize your business, get in touch with the expert team at our partner consultancy, Broadmind.ai. 💼 They specialize in offering tailored AI solutions. #AI #machinelearning #dataanalytics #colgatepalmolive #businessobjectives #data-driven #innovation #partnership For more information about how #AI can be used at your business - contact the team at our partner's consultancy, Broadmind.ai : www.broadmind.ai

Data science is one of the most demanding fields in the world due to several key factors: Data Explosion: The amount of data generated daily is enormous and continues to grow exponentially. Businesses and organizations need data scientists to make sense of this data, extract valuable insights, and make data-driven decisions. Decision Making: Data-driven decision-making is becoming crucial in nearly all sectors, from healthcare and finance to marketing and sports. Data scientists help organizations make informed decisions by analyzing data trends and patterns. Technological Advancements: The development of new tools, algorithms, and technologies in machine learning, artificial intelligence, and big data analytics has expanded the scope and capabilities of data science, making it a vital component of modern technology and business strategies. Competitive Advantage: Companies that leverage data science effectively can gain a competitive edge by optimizing operations, improving customer experiences, and innovating products and services. Interdisciplinary Applications: Data science is applicable in various domains such as healthcare (predictive diagnostics), finance (fraud detection), retail (personalized recommendations), transportation (route optimization), and many more. Career Opportunities: The demand for skilled data scientists far exceeds the supply. This gap in the job market makes data science a lucrative career option with high salaries and numerous opportunities for growth and advancement. Innovation and Research: Data science fuels innovation by enabling new discoveries and advancements in various fields through the analysis of large datasets and complex algorithms. #stats #Datasciecne #DSmostdemandingbranch #dataengineer #dataanalytics #powerbideveloper #tableudeveloper #dataset #YesPIET