Viseven Group is a leading global B2B MarTech service provider, empowering Pharma and LifeScience companies since 2009. Our mission is to drive digital transformation and excellence, offering comprehensive end-to-end software and digital marketing services tailored to the pharmaceutical industry. The company's solutions, products, and services are actively used by the top 100 Pharma and Life Science companies.
At Viseven, our rapidly growing team boasts over 700 highly skilled professionals, including experts in development, design, business analysis, project management, delivery, sales, marketing, and customer success.
With a global footprint in more than 30 countries across the US, LATAM, Europe, and APAC, and physical offices in Ukraine, Poland, Estonia, India, and the US, we are well-positioned to serve our diverse clientele.
Join us and become part of a pioneering team dedicated to shaping the future of digital transformation in Pharma and Life Sciences across more than 50 countries around the globe.
Responsibilities:Understand business objectives and developing models that help to achieve them, along with metrics to track their progressUnderstand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architectureAnalyse the ML algorithms that could be used to solve a given problem and ranking them by their success probability as well as analyse large, complex datasets to extract insights and decide on the appropriate techniqueBuild algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in productionApply machine learning algorithms and librariesExploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real worldVerifying data quality, and/or ensuring it via data cleaningSupervising the data acquisition process if more data is neededFinding available datasets online that could be used for trainingTraining models and tuning their hyperparametersAnalyzing the errors of the model and designing strategies to overcome themManage the infrastructure and data pipelines needed to bring code to production, deploying models to productionProvide support to engineers and product managers in implementing machine learning in the product.Collaborate with data engineers to build data and model pipelinesLiaise with stakeholders to analyse business problems, clarify requirements and define the scope of the resolution neededDevelop machine learning applications according to requirementsRequirements:Proven experience as a Machine Learning Engineer or similar roleUnderstanding of data structures, data modelling and software architectureDeep knowledge of math, probability, statistics and algorithmsDemonstrated technical expertise around architecting solutions around AI, ML, deep learning and related technologies.Developing AI/ML models in real-world environments and integrating AI/ML using Cloud native or hybrid technologies into large-scale enterprise applications.In-depth experience in AI/ML and Data analytics services offered on Amazon Web Services and/or Microsoft Azure cloud solution and their interdependencies.Experience in effective data exploration and visualization (e. g. Excel, Power BI, Tableau, Qlik, etc.)Familiarity with machine learning frameworks and librariesExcellent communication skillsAbility to work in a teamOutstanding analytical and problem-solving skillsThe ability to explain complex process to people who aren't programming expertsExperience with Amazone Cloud and AWS AI services English – upper-Intermediate and higherPrevious experience in communication with clients, ability to interact with clients freely, and consult them from a technical standpoint.Pharma domain backgroundWhat we provide:
We know our team members are key to achieving our goals, so we value and empower them to share their vision. We reward this passion with exceptional benefits, including:
Competitive Compensation: Regular performance-based salary and career development reviews.
Experienced Team: Join a passionate, experienced team in a friendly atmosphere.
Career Growth: Opportunities for professional and career advancement.
Paid Time Off: 18 business days per year (20 business days after 2 years of service).
Sick Leave:
Non-documented: 4 business days per year.
Documented: 20 business days per year.
Family Leave: 3 paid business days for marriage, childbirth, or bereavement.
Medical Insurance: Comprehensive coverage.
English Courses: Learning opportunities to improve your language skills.
Professional Development: Participation in forums and conferences.
Corporate Events: Regular team-building activities and events.
Work Environment: Enjoy a comfortable, fully equipped office and the possibility to work from home.
