Viseven Groupis an international IT company specialising in interactive content and cloud-based solutions for global pharmaceutical companies since 2009; constant growth and self-development is in our corporate DNA. Our unique developments and approaches are actively used in more than 50 countries all over the world. Viseven's solutions are represented at major industry events in Barcelona, Philadelphia, London, etc.
The rapidly expanding team includes more than 700+ highly-skilled tech- and non-technical experts: front- and back-end developers, BA specialists and managers who create, localize and customize applications at 8 offices: in Kyiv, Zhytomyr, Vinnytsia, Ternopil (Ukraine), Tallinn (Estonia), New Delhi (India) and Bridgewater (NJ, USA).Responsibilities:
- Understand business objectives and developing models that help to achieve them, along with metrics to track their progress
- Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture
- Analyse 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 technique
- Build algorithms based on statistical modelling procedures and build and maintain scalable machine learning solutions in production
- Apply machine learning algorithms and libraries
- Exploring 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 world
- Verifying data quality, and/or ensuring it via data cleaning
- Supervising the data acquisition process if more data is needed
- Finding available datasets online that could be used for training
- Training models and tuning their hyperparameters
- Analyzing the errors of the model and designing strategies to overcome them
- Manage the infrastructure and data pipelines needed to bring code to production, deploying models to production
- Provide support to engineers and product managers in implementing machine learning in the product.
- Collaborate with data engineers to build data and model pipelines
- Liaise with stakeholders to analyse business problems, clarify requirements and define the scope of the resolution needed
- Develop machine learning applications according to requirements
Requirements:
- Proven experience as a Machine Learning Engineer or similar role
- Understanding of data structures, data modelling and software architecture
- Deep knowledge of math, probability, statistics and algorithms
- Demonstrated technical expertise around architecting solutions around AI, ML, deep learning and related technologies.
- Experience with Amazone Cloud and AWS AI services
- 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 libraries
- Excellent communication skills
- Ability to work in a team
- Outstanding analytical and problem-solving skills
- The ability to explain complex process to people who aren't programming experts
- English upper-Intermediate and higher
- Previous experience in communication with clients, ability to interact with clients freely, and consult them from a technical standpoint.
- Pharma domain background
What we provide:We understand that our team members are essential to making our goals a reality, so we value and empower them to share their vision. And we reward this kind of passion with highly competitive compensation and exceptional benefits, such as:· Competitive compensation and regular performance based salary and career development reviews· Passionate experienced team, friendly atmosphere· Professional and career growth· Paid time off - 18 business days per year (20 business days after 2 years of cooperation) + national public holidays· Non-documented sickleave-4business days per year· Documentedsickleave- 20 business days per year· Family leave - 3 paid business days in case of marriage,childbirth or bereavement· English learning courses· Opportunities to participate in professional forums and conferences· Regular corporate events and team-buildings· Enjoyable working environment: comfortable and fully equipped office and possibility to work from home