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 Additional Information
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