Position: Head of Data Science
Company: SoftConstruct Ukraine
Category: Data Science
Experience required: 5y
English level: intermediate

**SoftConstruct Ukraine** is a large product company with Armenian roots.
We develop solutions in the fields of Big Data, Data Science and CryptoExchange. We combine our expertise in iGaming software development with advanced technologies to develop original software such as sports statistics, risk analysis, security. In most cases, we deal with atypical projects for the market, try to find and generate new technology-based solutions in our field.

We support our colleagues who actively participate in all spheres of our country’s defense, as well as help in the development of solutions, technical security support — the information sector of the state. We are ready to offer work for IT specialists who need it.

If you are looking for a Leading Role in Data Science direction and have relevant experience we would be more than happy to offer you our position **Head of Data Science.**

**SKILLS & EXPERIENCE**

**Technical skills:**

Must have:

- Knowledge of data modeling, feature engineering, and data preparation techniques.
- Experience in computer vision techniques such as object detection, segmentation, and tracking.
- Strong programming skills in Python and experience with data analysis libraries such as Pandas, Sklearn, Numpy, etc.
- Expertise in deep learning frameworks such as TensorFlow, Keras, or PyTorch.
- Knowledge of image and video processing techniques, such as feature extraction, optical flow, and image and video compression.
- Experience in natural language processing (NLP) and machine learning models for text classification and sentiment analysis.
- Experience in implementing and deploying recommendation systems.
- Experience in designing and implementing scalable, reliable, and efficient machine learning systems that can handle large-scale data processing.
- Familiarity with containerization technologies, such as Docker and Kubernetes, and cloud computing platforms, such as AWS, Azure, and Google Cloud Platform.
- Strong skills in data engineering, including data ingestion, transformation, and storage, as well as experience with distributed data processing frameworks such as Apache Spark and Hadoop.
- Proficiency in SQL. Writing efficient queries on large data sets.
- Experience with designing and implementing machine learning-based microservices and APIs that can be integrated into larger software systems or deployed as standalone services.
- Experience with model versioning, testing, and monitoring, including automated testing, continuous integration, and continuous deployment (CI/CD) practices.
- Understanding of ML Life Cycle (MLOps): Scoping, Data, Modeling, Deployment.
- Experience in code review process: Work with PR, be able to detect major issues in the code.
- Technical Project management: Project risks, How to estimate high level projects. How to organise a continuous delivery. Break down and arrange project tasks. Technical backlog. Time to market.

Nice to have:

- Experience with recommendation system evaluation metrics, such as precision, recall, and mean average precision (MAP).
- Experience with A/B testing and experimental design to evaluate the effectiveness of recommendation systems and iteratively improve them over time.
- Knowledge of real-time streaming data processing systems, such as Apache Kafka, and experience with building real-time machine learning systems.

**Soft Skills:**

Must have:

- Problem-solving: ability to analyze the cause of a problem and decide how to solve.
- Communication and Teamwork: a complex of negotiation skills, presentation skills, the ability to find compromises and work in a team.
- Time Management: ability to use your time productively and efficiently.
- Creativity and Proactive: ability to think about a task or a problem in a new or different way, ability to anticipate events so that he/she can take control of a situation and prepare for the situation ahead of time.

**Business Skills:**

Must have:

- Autonomy: being able to make, implement and review decisions based on appropriate techniques.
- Influence: abilities to encourage and persuade others to adopt your ideas.
- Complexity: Performs a range of work, sometimes complex and non-routine, in a variety of environments. Applies a methodical approach to routine and moderately complex issue definition and resolution. Applies and contributes to creative thinking or finds new ways to complete tasks.
- Attention to detail: ability to accomplish/complete a task while demonstrating a thorough concern for all the areas involved, no matter how small.

Nice to have:

- Efficiency: teams costs, save company’s money.

**People Management:**

Must have:

- Tech Leads mentoring.
- Team skills improvements: L&D, IDPs, Promotions, Salary review.

**GOALS & ASPIRATIONS**

- Ensuring that the department is delivering high-quality, stable, and scalable products that meet the needs of the organisation.
- Building and managing a team of skilled Data science specialists who are motivated and engaged in their work.
- Staying up-to-date with the latest trends in Data science and related technologies, and implementing them in the department’s work as appropriate.
- Building and maintaining strong relationships with other departments and stakeholders within the organisation, to ensure that the department’s work is aligned with the overall goals of the organisation.
- Managing the department’s budget and resources effectively, and ensuring that all projects are delivered on time and within budget.
- Continuously improving the department’s development processes and methodologies, to ensure that they are efficient and effective.
- Leading the department to consistently deliver projects that exceed customer expectations and contribute to the success of the organisation.
- Developing a team of highly skilled and motivated Data science engineers who are recognized as experts in their field.

**WHAT CAN WE OFFER YOU**

- The opportunity to lead a large technological direction, build and expand a strong Data science community in the company;
- Use your experience and knowledge to offer innovative approaches, thanks to which to work with challenges;
- Annual leave: 20 working days per year;
- All paid sick days with a doctor’s note (no limit on the number of times. But for 1 time it is paid up to 2 weeks);
- Registration in any format within Diia.City at the employee’s choice (Employment contract, Gig-contract);
- Individual English classes at EnglishDom online school (compensation within 50% of the amount of expenses);
- €450/year budget for training and / or sports (compensation within 50% of the amount of expenses) after probationary period;
- Corporate program of psychological support;
- Free health insurance after probationary period.