REF AIA-2021-02-006 – PowSys R&D Scientist job offer – 20210330

Grupo AIA specializes in advanced software development based on optimization, simulation, and Machine Learning techniques (classification, forecasting, etc.), both on Big Data and traditional databases, through basic science methodologies, mainly from Mathematics and Physics. Grupo AIA focuses on the transformation of information into useful knowledge, to provide our customers a rigorous data-based support for their decision-making, at all operational and managerial levels.

Grupo AIA is currently seeking a Power Systems R&D Scientist who is willing to make a professional career in a growing company specialized in the solution of complex problems in the industrial and business sectors through the application of advanced technologies. We offer you to work at the forefront of cutting-edge innovation projects for some of the major companies in the country. Our main target sectors are banking, energy, retail, and biotech. We also participate in advanced R&D projects such as Quantum technologies. You can see some of our projects on our website, http://aia.es.

 

What is expected of you and what are the deliverables involved

You will work as R&D Scientist on projects for the Energy Unit in AIA, mainly in tools and consulting for the operation and network planning of power transmission grids: modeling, analysis, simulation, optimization, etc.

 

Job responsibilities:

  • Develop/expand/refine models of power equipment in the field of network simulations, both static (power flow) and time domain (quasi-EMTP), and their implementation in simulation tools of large electrical companies.
  • Develop testing & validation codes, both at the Unit Testing level and at the global (functional) level of the simulation tools.
  • Review the latest advances in the scientific literature of this field, evaluate whether they apply, and quickly learn how to take advantage of them.
  • Analyze and report results in the technical language used by the electric engineers of our client companies.
  • Interact with the client (power company) in order to understand the business needs, both at the operational and the analytical level, as well as the technological IT environment in which the solution is to be deployed.
  • Propose the most suitable methodology, evaluating implementation feasibility case by case.
  • Present individual work to the team and commercial presentations to customers.
  • Identify possible new projects or project extensions to existing ones.

You will have the support and knowledge of the AIA’s Energy team, which will accompany you along with the implementation of projects. In turn, AIA expects of you:

  • A strong basic background in Physics or Electrical Engineering. Specialization in power transmission is not required, but we expect fast learning in this area.
  • A strong training or proven experience in programming.
  • Strong analytical and high comprehension skills, together with a results-driven attitude to solve real business problems.
  • A proactive person, capable carrying out work either autonomously or as a teamwork player, depending on each project needs.

As part of the Energy team of AIA, you will enjoy a stimulating environment with your colleagues to share, learn and apply the latest technological advances in AI and power grid networks. You will also be able to be in contact with experts at client companies and learn the ins and outs of their businesses, while experiencing the satisfaction of seeing how your work solves the problems they pose.

 

Minimum Requirements

  • Bachelor Degree / Physics or Electrical Engineering
  • Training / proven experience (> 1 year) in programming (any language), preferably in areas related to algorithms or numerical methods
  • Advanced level of English

 

Experience/Skills desired

The following list items are not essential but will be highly valued:

  • PhD (in any area)
  • Experience in power grids
  • Programming experience in any of the following languages: C, Fortran, Java, Python, MATLAB
  • Experience in the Modelica language
  • Experience working in technological innovation environments for any business sector
  • Communication skills to convey complex ideas
  • Passion for keeping up to date with the state of the art in Science & Technology in general

 

 

REF AIA-2021-02-005 – Data Scientist job offer description – INNO

Grupo AIA is specialized in advanced software developments based on optimization, simulation and Machine Learning techniques (classification, forecasting, etc.), using both Big Data and standard databases, and applying basic science methodologies, mainly from mathematics and physics. Grupo AIA´s striving objective is to transform information into useful knowledge to give our customers rigorous support for decision-making at all operational and management levels.

Grupo AIA is currently looking for a Data Scientist willing to develop a professional career in a growing company specialized in solving complex problems in the industrial and business sectors through advanced technologies. We offer you the opportunity to work at the forefront of cutting-edge innovation projects for some of the major companies in the country. Our main target sectors are banking, energy, retail, and biotech. We also participate in advanced R&D projects such as quantum technologies. You can see some of our projects on our website, http://aia.es.

 

What do we expect from you and what are the deliverables involved?

You will work as Data Scientist on projects for the Innovation Unit in AIA. Your job will consist in:

  • Developing AI/ML models for forecasting, classification, and optimization tasks.
  • Interacting with final customers to ensure full understanding of their real needs, business model, and technological environment.
  • Proposing the most suitable methodology, keeping in mind the project´s feasibility according to each customer´s constraints.
  • Presenting individual work to the team and commercial presentations to customers.
  • Identifying possible new projects or project extensions of existing ones.

You will have the support and knowledge of the Innovation Team of AIA, which will accompany you along with the implementation of such projects. In turn, we expect from you:

  • Fast- prototyping skills.
  • Capacity to identify gaps in existing algorithms/libraries and to develop specific solutions to solve them.
  • Results-driven, strong analytical skills, and a high level of understanding for structuring and solving real business problems.
  • Being proactive and having the ability to work either autonomously or as part of a team, depending on the needs of each project.

Being part of the Innovation unit of AIA will let you enjoy a stimulating environment with your colleagues to share, learn and apply the latest technological advances in AI. It will also allow you to be in contact with different sector experts, learn from them the insights of their businesses, and enjoy applying your technical skills to solve the proposed problems.

 

Minimum Requirements:

  • PhD in Science (preferable, but not exclusively, in Physics, Mathematics, Computer Science).
  • Experience in Data Science (> 1 year).
  • Experience in Python and SQL.
  • Advanced level of English.

Desired experience/skills:

The following items are not essential, but will be highly valued:

  • Experience in Big Data environments (including cloud).
  • Experience interacting with Data Engineers to ensure that the technological environment of the clients is understood, and proposing the suitable methodology and solutions.
  • Management experience with teams of Data Scientists/Analysts.
  • Communication skills to convey complex ideas.
  • Passion for keeping up to date with the state of the art in AI/ML.

Contact:

Jordi Nadal – nadalj@aia.es

 

Aplicaciones En Informática Avanzada, Sociedad Limitada. Ordinary and extraordinary general shareholder’s meeting

Mrs. Regina LLopis Rivas, as the Sole Administrator  of the company  APLICACIONES EN INFORMÁTICA AVANZADA, S.L., convenes the Ordinary and Extraordinary General Shareholder´s Meeting

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computing

Grupo AIA takes part in the DNA project developed by Adolfo Domínguez

Adriana Domínguez, as executive president of Adolfo Domínguez, made public in an online press conference last June 19th, the DNA project kick-off in which Grupo AIA has participated as the technological provider. Based on Artificial Intelligence, a recommendation algorithm combined with the experience of Personal Shoppers of Adolfo Domínguez, have allowed them to choose clothe items and accessories, adapted to each of its customers, and send them to their homes without trying them on or going to a shop.

Grupo AIA is pleased to have participated in the project for the retail sector and provided its 30 years´ experience in the development of Artificial Intelligence based applications and data analytics. This Project opens up.new collaboration opportunities between Adolfo Domínguez and Grupo AIA, as the Spanish fashion firm has showed its commitment to innovation as the way to improve its relationship with its customers.

Access to the new DNA service at https://www.adolfodominguez.com/es/adn.

software grupo AIA-ASISA

ASISA and Grupo AIA agree to develop jointly AI-based software

Grupo AIA and ASISA have signed an agreement to develop jointly artificial intelligence-based software aiming at improving efficiency and dynamism of the insurance company´s management processes and ultimately to meet its customers and insurers´ needs.

The project´s kick-off between Grupo AIA and ASISA, a leading health insurance company with the best Net Promoter Score, NPS[i], is aimed at developing innovative software based on basic science (Physics and Mathematics) and Data Science to meet their business needs. This knowledge transfer will enable Grupo AIA to provide intelligence to ASISA´s business processes through advanced analytics methodologies such as Machine Learning.

Grupo AIA focused on solving management efficiency of medical actions at this phase of the collaboration project, will deploy a Machine Learning-based tool that will make medical actions management more efficient and ASISA will be able to make wiser decisions that will benefit its customers. Grupo AIA´ s contribution based on the state-of-the-art Artificial Intelligence technology will help to improve the insurance company´s management and control processes in this business area.

This collaboration project is framed within ASISA´s technological transformation across business processes impacting on both, welfare and management activities´ efficiency and effectivity improvement as well as customers´ satisfaction. The ultimate goal of this process for the company is to provide customers a total digital service including the whole process from services contracts to their management.

[i] Braintrust ´s Observatory of Health Competence.

COP25-cumbre-clima

Regina Llopis participates at the Climate Change World Summit

What can women contribute to climate change prevention?  Based on this premise, a round table was held at the green zone of the Climate Change World Summit in Madrid, COP25, with the special participation of influential women from different fields to discuss Climate Change problems and how they could help to combat it.

Regina Llopis, president of Grupo AIA, Andrea Barber, cofounder and CEP of Rated Power; Mari Luz Cádiz, researcher at Universidad de Oporto); Patricia Fernández, researcher at Centro de Biotecnología y Genómica de Plantas, (UPM-INIA); Cristina Romera, researcher at the Instituto de Ciencias del Mar (CESIC) and moderated by Ángeles Heras, Secretary of State for Universities, Research, Development, and Innovation have participated at this round table and was promoted by the Women Observatory, Science and Innovation.

A variety of problems and challenges facing the planet were exposed at this Climate Summit.  Among the solutions proposed, Cristina Romera has mentioned the research done on plastic recycling and new materials to replace the oil by-product. Patricia Fernández explained how the research on plants is combating pests and allowing the formulation of new pesticides based on plants´ natural defense mechanisms, so efforts have been made towards intelligent and sustainable agriculture.

However, implementing these ideas would entail moving from the research area to the business one, and knowledge transfer to the industry to implement the changes required against climate change. On this issue, Regina Llopis, president of Grupo AIA, reminded the slim participation of women in entrepreneurship.

Regina Llopis highlighted that only 7% of the capital risk in Europe goes to businesses created and managed by women and in Spain, only 8% of women are business angels, in other words, investors at the first stages of the business development.

These figures show the low participation of women in the business world and the also president of WA4STEAM has urged women to be involved in climate change combat through the creation of technological-based businesses. Areas such as artificial intelligence, Physics, Mathematics, or Engineering allow promoting a more sustainable world.

artificial intelligence drugs

Artificial Intelligence for new drugs discovery

Biomedical science innovation based on AI technology is the long-awaited opportunity for achieving higher effectivity in this industry. New drug development through R&D innovation in a shorter time and at a lower cost is the Holy Grail of the biopharmaceutical industry.

Scientific innovation not only involves finding the molecular mechanism of a disease but also the development of new drugs for the cure, palliation or prevention of diseases.

Innovation in the pharmaceutical industry costs over 2.400,00 million euros, according to Farmaindustria. On the other hand, R&D global investment in the pharmaceutical sector accounts for 30.000,00 million, only in Europe and these figures hikes to 142.000,00 euros worldwide.

From this amount, 57% goes to design, development and clinical tests evaluation phases. The remaining 40% goes to basic research, approval processes and pharmacovigilance.

According to data provided by Biopharmaceutical representatives, developing a new medicine takes about 12 to 13 years from its discovery to its clinical use in patients. However, only a few molecules reach the commercialization phase. Many are left behind along the phases of the drug development process.

It´s precisely in drug targeting discovery and designs that AI-based techniques have cut downtime by half and costs by 25% in the production of new drugs.

Currently, the Spanish biopharmaceutical, Sylentis, has implemented a software based on Neural Networks, SVM and Machine Learning to gather, filter and reinterpret experimental data generated by the pharmaceutical industry. This allows them to enhance and develop the drugs thanks to a  software that trains to generate thousands of specific compounds to deal with a disease in a matter of a few days. The pharmaceutical company reduces the expensive and time- consuming task of candidate´s selection from years to only a few days.

AI for personalized drugs.

A survey conducted by Deloitte and MIT Sloan Management Review last June found out that only 20 % of biopharmaceutical companies are digitally mature enough, and the lack of a clear vision, leadership and financing are slowing down companies´ growth.

According to MarketsandMarkets, AI´s demand in the biopharmaceutical industry is expected to grow from US$ 198.3 million in 2018 to US$ 3.88 billion in 2025.

The four projected areas to drive most of the AI market forward in biopharmacy between 2018 and 2025: drugs discovery, precision medicine, diagnostic imaging and medical diagnosis and research. The report says drugs´ discovery reached a larger market share during the survey period.

These areas that go from the target candidate molecules selection to the production of the new drug provides a unique opportunity to speed up drugs development. The potential improvement of the process includes:

  • Process redesign to speed up new molecules discovery time and is based on expert knowledge.
  • Digitalization of repetitive processes automation and generation of new content and data.
  • Advanced analytics incorporating internal and external sources. Here new predictive model would be included.

A key role for AI algorithms is molecules interaction forecasting to find the disease mechanisms. In turn, these mechanisms could help setting new biomarkers to identify, design, validate and optimize new drugs candidate target and identify existing drugs that could be reused for other indications

 

Vicens-gaitan-Negocio

Vicens Gaitán, CDS in Grupo AIA: “AI allows us to exploit information better than ever before”

What are AI key points? Are AI-driven companies getting a competitive advantage? At the conference round table held last September at La Salle, “Artificial Intelligence. Why & How to keep your Company alive” were raised these questions and sparked lively discussions thanks to speakers´ participation: Vicens Gaitán, Chief Data Science in Grupo AIA, Pier Paolo Rossi, Advanced Customer Marketing & Analytics Director in Banc Sabadell and Daniel Marco, Department for Digital Policy and Public Administration of Catalonia.

Digital Transformation has become a turning point in companies´ work culture, particularly in data management and AI-based technology to achieve their competitive advantage in their industrial sectors.

However, during the speakers´ interventions at the conference, it was made clear implementing AI was not setting an “automatic pilot”, but instead it involved having essential key elements.

Above all, being able to implement AI to the business to meet specific needs leading to more intelligent decision-making. Vicens Gaitán, Chief Data Science in Grupo AIA, pointed out that “thanks to the implementation of artificial intelligence techniques in companies, these companies can be trained to exploit data as never before”.

In other words, data-driven companies striving for the best and more efficient decision-making must work on these four big areas:

  • Knowing the dataset location and capture it. Data management time must be adequate for accurate and suitable subsequent decision-making fitted to each business case.
  • Dataset creation and assembly
  • Apply the algorithm that will extract information from the data.
  • Make decisions based on results provided by the algorithms.

One of the most sensitive aspects at the conference was the need for customer-centric decision- making for more effective results. Consequently, technology should go hand by hand with the business to lead customer-centric projects.

Artificial intelligence techniques enhance businesses’ capacities to adapt and anticipate strategic and tactic decision making to their real customers´ demand. Therefore, it is essential that the business and Big Data teams work together to achieve business intelligence.

The degree of maturity of Artificial intelligence-driven businesses is based on their capacity to integrate AI as their main structure. The greater artificial intelligence, the greater the corporative intelligence.

 

data translator

The hidden figure behind a successful AI implementation in the organizations.

The Artificial Intelligence implementation in companies is cross functional: Marketing, Finance, Operations… they all have benefited from the emergence of data driven across business processes in their organizations.

In a recent study published by Fujitsu and Pier Audoin Consultants, shows that the benefits companies have gained through Artificial Intelligence implementation are starting to pay off. This is not a matter of five years´ time. The AI´ s time has come. However, the figures are still low: only 11% of the surveyed companies are implementing AI strategies, 29% have AI projects in progress and 35% expect to do it in the next two years.

Under this classification, they would be defined as innovators, early adopters, followers. In other words, based on the company´s maturity and data adaptation, they will belong to one of the groups before mentioned.

Accordingly, 53% of the companies that have implemented AI or have in mind doing it believe improvement of automation processes depends on it, whereas almost 75% are creating business units for AI´s implementation take-off. The main areas this technology is implemented on is higher production efficiency, maintenance forecasting and above all, in customers´ behavior forecasting for appropriate business actions.

Nevertheless, a survey delivered by MIT Sloan Management Review and Boston Consulting Group a few weeks ago highlighted different data.

Although it claims AI´s rewards promise, these are not risk-free for example, a competitor taking the risk and going a step ahead. These are the innovators that use AI for the company´s across business processes alignment, investment and integration.

Many leading companies see AI not as an opportunity but as a risk strategy.  And this perception has gone up from 37% to 45% from 2017 to 2019 respectively.

Concerning risk management, many AI based initiatives have failed. Seven out of ten of the surveyed companies claimed they have hardly benefited from this technology. And it´s not a trivial matter when almost 90% of companies have invested in AI.

Thus, even if some companies have found out success with AI, most struggle to add value based on it. As a result, many executives face challenges associated with AI: It´s a source of non- exploited opportunities, an inherent risk. But, above all, it´s an urgent issue to tackle. How can executives exploit the opportunities, manage risks and minimize AI associated problems?

Data translator: the hidden figure

Professionals training, not only in technical and scientific areas but also in communication and interpretation, becomes essential for the differential AI value generation. Deep understanding of the business needs and knowing how to convey that to the technical teams in charge of implementing AI is the Holy Grail of all the companies and providers of this service.

On the other hand, Mckinsey says that success results based on AI and data analytics do not depend only on data scientists, data engineers or data analytics teams. A transversal figure is required: a data translator.

Mckinsey believes this figure can ensure the organizations achieve real impact from their analytical initiatives as it can help to understand correctly the business needs and translate them into a scientific -technical language and vice versa.

Data translation experience allows this figure to get deep knowledge of the core business and its value chain in diverse areas: distribution, health, marketing, manufacturing or any other environment.

As the consulting company defines it, in their role, translators help to guarantee deep knowledge generated through sophisticated analytics is translated into impact at every level of the organization. By 2026, The Global McKinsey Institute estimates translators demand will reach two or four million only in the U.S.

Thus, translators take advantage of their insights in AI and analytics to convey these commercial objectives to data professionals who will create the models and the solutions. Finally, the translators ensure the solution produce the insights the company can interpret and execute and ultimately, communicates the benefits of these insights to the businessmen to boost adoption.

One way to reduce the risk strategy companies have taken when they decide to be ahead of their competitors in their sector, is without any doubt, the capacity to interpret the data and offer insights based on them.

 

 

IDENTIDAD-CLIENTE

Artificial Intelligence for Customer’s identity

When customers know what they want, companies must figure out what it is. However, according to Gartner, CMOs only invested 29% of their budgets in new technologies to meet their needs.

Probably marketing specialists do not have the appropriate technology or the technology they have isn´t enough. However, often marketing departments do not have full knowledge of the capabilities of the technologies they have paid for and consequently, do not take advantage of them.

To guarantee a high return of the investment for the business (ROI) the marketing specialists should start by auditing their technological ecosystem in their organizations to finally set the best ROI strategy.

However, the assumption that having a specific technology will guarantee to make money, is a common mistake. According to a survey conducted by the consultant company McKinsey, the technological gap between leading companies and others staying behind is growing. This means companies that make data-driven decisions will make the difference as compared to the rest of companies that are still struggling for basic data analysis and technology.

For both, innovating companies and the ones lagging behind, data analytics emerges as an opportunity to offer better insights, in other words, having a healthy data culture. Some will implement it and others will not. Therefore, some will obtain a higher ROI at the expense of companies that will lag behind as they will not implement a data-driven culture.

Once a healthy data-driven culture and appropriate technology are implemented, the time to listen to customers has come. As said before, the more consumer’s attention is captured, the more customer’s personalization will grow. The marketing departments invest around 14% of their budget to achieve the so long waited for personalization, very little in return for what it offers.

AI-based Customer identity

The need to know customers opens the adoption and use of AI not only at marketing scale but also at a broader and general level in the organization. The survey conducted by McKinsey Global Institute containing more than 3000 companies called “Artificial Intelligence: The next digital frontier?” shows that the first AI users are closer to the digital frontier. It´s precisely at this frontier where the leading companies in each sector are found. AI is present in all the groups, at the core business of the value chain, it is used to boost revenues, reduce costs, and has total executive management support. The companies that have not adopted AI technology at a certain scale or at the core business, are not sure of the revenues they could expect with such an investment.

Innovative companies know that existing and future customer personalization is achieved by customer’s knowledge. Here is where AI is introduced completely, and marketing specialists are trained to identify each one of them and personalize their actions.

One of the key elements of the customer’s identity techniques is that it allows us to characterize actionable concepts. These actionable concepts are the result of incorporating the business expert knowledge to the AI, also called Intelligent Observation Systems. The result is a set of concepts providing a broader customers perspective.

Therefore, customer’s identity techniques enable companies to obtain, for instance, better insights into consumer’s habits. Once they are identified, the different areas of the organization have enhanced the ability to make personalized offers leading to a greater benefit while delivering greater levels of customer satisfaction. For example, churn may be avoided once the customer’s satisfaction is analyzed. Additionally, price predictive models for certain products can be set.

Innovative companies are the ones able to respond to the classic questions: How do my customers behave? What value of information can I obtain from their habits? How can I improve the companies´ revenues? Partly, it´s due to their capacity to be always at the state of the art.