We are looking for a Data Scientist. This role is focused on delivering end-to-end data science solutions that generate measurable business value. The Data Scientist will lead the full lifecycle of AI/ML initiatives, from initial data acquisition and exploration through model development, deployment, and long-term operational monitoring.
Working closely with business stakeholders, engineers, and domain experts, the role involves designing predictive models, probabilistic frameworks, and advanced analytics solutions embedded into production systems.
A key part of the role extends beyond deployment, requiring ongoing validation of model performance in real-world environments, identifying gaps through Root Cause & Corrective Action (RCCA) analysis, and defining continuous improvement roadmaps. The position combines strategic thinking with hands-on execution to ensure AI/ML solutions remain effective and aligned with evolving business objectives.
Innovecs is a global digital transformation tech company with a presence in the US, the UK, the EU, Israel, Australia, and Ukraine. Specializing in software solutions, the Innovecs team has experience in Supply Chain, Healthtech, Software & Hightech, and Gaming.
For the fifth year in a row, Innovecs is included in the Inc. 5000 and recognized in IAOP’s ranking of the best global outsourcing service providers. Innovecs is featured in the Global Top 100 Inspiring Workplaces Ranking and won gold at the Employer Brand Management Awards.
Our value to you:
- Flexible hours and remote-first mode
- Competitive compensation
- Complete Hardware/Software setup – anything you need for work
- Open-door culture, transparent communication, and top management at a handshake distance
- Health insurance, vacation, sick leaves, holidays, paid maternity/paternity leave
- Access to our learning & development center: workshops, webinars, training platform, and edutainment events
- Virtual team buildings and social activities
If you feel like you’re the perfect match for this role, drop us your CV!
There are no limitations, no barriers when the right people are on your way — apply for the vacancy and succeed with us
Innovecs is an equal opportunity employer. All hiring decisions are based on professional qualifications, skills, and experience. We are committed to a transparent, merit-based recruitment process that prevents discrimination and ensures equal opportunities for all candidates. Reasonable accommodations are available upon request throughout the recruitment process to support accessibility and inclusion.
- 5 years of practical experience delivering data science solutions in real-world business contexts
- Strong programming skills in Python with a focus on clean, maintainable, and reusable code
- Advanced SQL capabilities and hands-on experience working with large, unstructured, or inconsistent datasets
- Solid foundation in mathematics, statistics, and machine learning methodologies
- Proven experience deploying and maintaining machine learning models in production environments
- Ability to translate complex business challenges into structured analytical problems
- Strong communication skills, with the ability to clearly present insights to non-technical stakeholders
- Business-oriented mindset with a clear understanding of how analytical outputs translate into value, trade-offs, and growth opportunities
- Practical experience with Azure-based tools for model development, deployment, and lifecycle management
- Continuous learning mindset with interest in emerging AI/ML techniques and technologies
- Apply advanced AI/ML methods to solve business and customer problems
- Design, develop, and scale machine learning models and prototypes suitable for production integration
- Partner with engineering, product, and business teams within Agile delivery environments
- Take end-to-end ownership of models, ensuring performance, reliability, and continuous enhancement across their lifecycle
- Contribute to full-cycle development, including feature engineering and production readiness
- Review code, provide peer feedback, and maintain high engineering and quality standards
- Build and maintain strong working relationships with internal stakeholders and external partners
- Convert complex analytical outputs into clear, actionable insights for both technical and non-technical audiences
- Decompose ambiguous business challenges into well-defined data science problem statements
- Stay up to date with industry advancements in AI/ML and actively apply new knowledge
- Collaborate with other data science teams to strengthen standards, practices, and culture
- Produce and maintain comprehensive documentation for models, workflows, and processes to support transparency and knowledge sharing
