Jobs Data & Analytics

About the company

Are you tired of missing important moments in your weekly game because no one recorded you? Say goodbye to FOMO and hello to PUSHIT!

PUSHIT allows you to easily catch up on all the highlights you did while playing your sports game.

Our advanced replay system allows you to capture moments previously taken, so you never have to miss anything.

See those videos for more information about PUSHIT:

1. https://www.youtube.com/watch?v=uQrXgheKjCg
2. https://www.youtube.com/watch?v=pmdihAft2f8

See our current mobile apps:

1. IOS
2. Android

What is the job

You’ll be the Machine Learning Engineer on a compact, fast-moving team, working directly with the founders. Your mission: design, train, and ship computer-vision models that recognize sports events and generate highlight videos—running both in the cloud and on edge devices.

Responsibilities

• Build & improve CV models – object detection, action recognition, semantic segmentation, tracking, and event classification for multi-camera sports footage.
• Optimize for the edge – convert and quantize models (TFLite/ONNX/RT-Core) so they run in real time on Raspberry Pi 5 and ARM-based phones.
• Own the ML pipeline – data collection, labeling guidelines, experiment tracking (Weights & Biases / MLflow), automated training, and CI/CD to Kubernetes.
• Collaborate cross-functionally – work with backend, video-encoding, and mobile teams to integrate inference results into our NestJS APIs and Flutter/Angular clients.
• Raise the bar – research state-of-the-art techniques, run ablation studies, author technical specs, and mentor future student interns.

Requirements

• Strong Python (3 yrs+) and deep-learning expertise with TensorFlow and/or PyTorch.
• Solid background in computer vision: convolutional nets, attention mechanisms, spatio-temporal models (e.g., I3D, SlowFast).
• Experience deploying models to mobile or edge hardware (TFLite, Core ML, TensorRT, or similar).
• Familiarity with Docker & Kubernetes workflows for scalable training/inference.
• Proven ability to turn research into production code: at least one project or product in the wild (GitHub, app store, or academic publication).
• Comfortable with version control, code reviews, agile tickets, and writing clear documentation.
• Passion for sports—or at least enough curiosity to spot a backhand winner or a slam-dunk replay!

• English—professional level (our dev team is global).

   

Bonus points

• Experience with video encoding pipelines (FFmpeg, HLS, RTMP) or real-time streaming protocols.
• Knowledge of AWS/GCP services for training at scale (SageMaker, Bedrock, Vertex AI).
• Skills in data annotation tooling or active-learning strategies to shrink labeling budgets.
• Background in satellite or aerial image segmentation, sign-language or face-recognition projects (great analogies to sports CV challenges).

• Love for open-source: contributions to CV libraries.

   

Why PUSHIT?

• Ship features that thousands of weekend athletes use every day.
• Work on cutting-edge CV problems with real-time performance constraints.
• Small team ⇒ huge ownership, zero bureaucracy.
• Fully remote
• Competitive salary, early equity, and budget for conferences & GPUs.

About the role and product:
We are looking for an experienced Data Engineer to join the Data &AI team delivering enterprise-grade data platform capabilities. The role centres on building Python-based ETL pipelines across a Medallion architecture, developing and operationalising data quality rules using both Python and the Informatica platform (IDQ, EDC, Axon), and ensuring robust governance integration. 

Responsibilities:
- Design, build, and maintain Python-based ETL pipelines across Bronze, Silver, and Gold layers following the Medallion architecture pattern.
- Develop and operationalise data quality (DQ) rules in Python, covering validity, completeness, consistency, uniqueness, accuracy, and timeliness dimensions.
- Build and maintain DQ rules using Informatica IDQ 10.5 on-premises, including mapplet design, profile configuration, and scorecard setup.
- Support data cataloguing and lineage activities using Informatica EDC, including schema scanning, data classification, and lineage mapping.
- Configure and maintain Informatica Axon for governance workflows, business glossary management, policy enforcement, and surfacing DQ scores to stakeholders.
- Develop cross-system DQ checks including referential integrity, reconciliation, and entity deduplication as scheduled Python jobs.
- Integrate DQ outputs into Power BI dashboards, contributing to the DQ Index Aggregation layer that unifies IDQ scorecard and Python-based scores.
- Support the IDQ–Axon integration, including Axon Agent configuration and DQ metric propagation into Axon dashboards.
- Contribute to the Python DQ framework package, maintaining modular, testable, and well-documented code with comprehensive unit test coverage.
- Support Talend-based ingestion processes at the Bronze layer, ensuring schema conformance and completeness checks.
- Participate in root-cause analysis of DQ failures using the programme’s three-tier classification taxonomy.

Requirements:
- Strong Python development skills, including experience with data processing libraries (pandas, PySpark) and testing frameworks (pytest).
- Hands-on experience with Informatica IDQ 10.5 on-premises: Developer Tool, mapplet design, profiles, scorecards, and expression-based DQ rules.
- Working knowledge of Informatica EDC for schema scanning, data lineage, and data classification.
- Experience with Informatica Axon for governance, business glossary management, HITL steward workflows, and DQ score surfacing.
- Solid understanding of the Medallion architecture (Bronze / Silver / Gold) and data lake design patterns.
- Working knowledge of SQL and relational databases for data validation and reconciliation.
- Experience building production-grade Python ETL pipelines with appropriate logging, error handling, and modular design.
- Experience with CI/CD practices for data pipelines and version control (Git).

Nice to have:
- Familiarity with Talend for data ingestion workflows.
- Exposure to AI/ML techniques for data quality: anomaly detection, entity resolution, DQ score aggregation.
- Experience generating or consuming Informatica IMX-format XML programmatically.
- Knowledge of Power BI for building or maintaining DQ score dashboards.
- Understanding of data governance frameworks, stewardship models, and regulatory reporting requirements.
- Experience with the Informatica IDQ–Axon integration bridge (Axon Agent setup and configuration).

The client offers:
- 24 working days of annual leave.

- 10 sick days.

- All official Ukrainian public holidays are days off.

- All necessary equipment for work is provided by the company.

- Medical insurance after the probationary period (3 months).

- Monthly budget to cover English classes, sports, and psychological support.

- All accounting and payroll administration are handled by the company; salary is paid net in UAH

We are looking for a Business Data Analyst to join a new B2C iGaming startup focused on the CIS market.

The project is currently at an active launch stage, so we need an analyst who already understands online casino economics, player behavior, and core iGaming metrics and can help build the business and product analytics function from the ground up.

📊 Responsibilities

• Build and develop business and product analytics from scratch
• Analyze key iGaming metrics: GGR, NGR, FTD, Deposits, ARPU, LTV, Retention, Conversion, Churn
• Analyze the player funnel: Registration → FTD → Repeat Deposit → Retention
• Perform cohort analysis and player segmentation
• Identify growth opportunities, anomalies, trends, and reasons behind KPI changes
• Analyze the effectiveness of bonuses, CRM campaigns, promotions, and VIP segments
• Build dashboards and regular management reporting
• Prepare actionable insights and recommendations for Product, Marketing, CRM, Finance, and Management
• Support business decisions with data and ad-hoc analysis

🎯 Must-have

• Hands-on experience in Business / Product / Data Analytics within iGaming
• Direct experience with B2C Online Casino
• Strong understanding of casino economics and metrics such as GGR, NGR, FTD, LTV, Retention, ARPU, Deposits
• Confident SQL skills and experience working with large datasets
• Experience with Power BI, Tableau, Looker, or similar BI tools
• Strong analytical thinking and ability to turn data into clear business conclusions and recommendations

➕ Nice to have

• Experience building analytics, reporting, or BI infrastructure from scratch
• Experience with CIS GEO
• Experience working closely with Product, CRM, Marketing, Finance, or VIP teams in iGaming

💻 Conditions

• Remote
• GEO: CIS
• Industry: iGaming / B2C Online Casino
• Project: new startup / launch stage

This role offers an opportunity to join the project at an early stage, directly influence how analytics is built, and work with data that drives product and business decisions.

Description

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.

The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.

The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.

OU’s: Currently, Nuero, Cardio, Diabetes is the OU that HDP data platform is working with, but there could be more OU’s coming up with requirements in future.

GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements

As a System Engineer within the Company Research & Systems Engineering team, you will have the opportunity to work on cloud-based solutions with a strong focus on AWS, Data Engineering, and scalable data platforms. You will collaborate with cross-functional engineering teams to design, develop, integrate, and maintain reliable cloud-native systems and data workflows.

In this role, you will contribute to building and evolving AWS-based architectures, data processing pipelines, and integrations across distributed systems. You will develop a strong understanding of end-to-end system architecture, data flows, infrastructure, and operational requirements, helping to drive technical implementation and delivery throughout the software development lifecycle.

You will work closely with software engineers, data engineers, architects, and other stakeholders to ensure that solutions are scalable, secure, maintainable, and aligned with both technical and business requirements.

• 3+ years of experience in System Engineering, Software Engineering, Cloud Engineering, Data Engineering, or a related technical role.
• Strong software development experience with Python.
• Hands-on experience designing, developing, or supporting solutions on AWS.
• Experience with data engineering concepts and technologies, including data ingestion, ETL/ELT, transformation, validation, and data processing pipelines.
• Strong SQL skills and experience working with relational and/or NoSQL databases.
• Experience with REST APIs, service integrations, and distributed application architectures.
• Understanding of cloud-native architecture principles and modern software development practices.
• Experience troubleshooting applications and distributed cloud systems and performing root cause analysis.
• Experience with Git and modern CI/CD development workflows.
• Strong analytical and problem-solving skills with the ability to understand complex systems and data flows.
• Ability to work effectively with software, data, cloud, and machine learning engineering teams.
• BA/BS in Computer Science, Software Engineering, Information Technology, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience with AWS data services such as S3, Glue, Athena, EMR, or similar technologies.
• Experience with Amazon SageMaker and machine learning development or deployment workflows.
• Experience with Infrastructure as Code using AWS CloudFormation, Terraform, or AWS CDK.
• Experience with AWS monitoring and observability services such as CloudWatch and CloudTrail.
• Experience working in Agile/Scrum development environments.

Job responsibilities

• Work with engineering and cross-functional stakeholders to gather, analyze, clarify, and document business, functional, and non-functional requirements, translating them into clear system and technical requirements.
• Define system requirements, interfaces, data flows, integration requirements, acceptance criteria, and technical constraints for cloud-based software components, data platforms, and integrations.
• Maintain requirements throughout the development lifecycle, ensuring traceability between business needs, system requirements, technical design, implementation, and validation.
• Identify gaps, dependencies, assumptions, and potential technical risks in requirements and work with stakeholders to resolve them before and during implementation.
• Design and contribute to scalable AWS-based architectures supporting data ingestion, processing, transformation, storage, and distribution.
• Analyze data and system behavior to support architecture, implementation, performance, and product decisions.
• Collaborate with Data Engineering, Software Engineering, Cloud Engineering, DevOps, and Architecture teams to design and integrate end-to-end cloud solutions.
• Support operational monitoring, logging, alerting, and troubleshooting of cloud applications and data processing workflows.
• Contribute to system architecture and technical design discussions, including scalability, reliability, security, performance, and cost considerations.
• Participate in technical and requirements reviews to ensure solutions meet defined requirements, engineering standards, cloud best practices, and established software development processes.
• Support continuous improvement of cloud infrastructure, data pipelines, deployment processes, requirements management, and engineering practices throughout the software development lifecycle.

Data Engineer / Migration Specialist (SAP BW to Databricks) 📊🚀
 

ZentixSoft is looking for a Senior Data Engineer! 🚀
 

Format: Full-Time Outstaffing, long-term engagement starting Dec 2026 / Jan 2027 through Q1 2028 (EU-based candidates).
 

💡 Why ZentixSoft? 
💸 Salary Review: A structured system of compensation reviews aligned with your engineering growth. 
⚖️ Work-Life Balance: Sustainable workflows with no senseless overtime, helping you keep your resource fully charged.
 🦾 Trust and Transparency: Zero micromanagement and no invasive time-trackers—we fully trust your professional autonomy. 
🎁 Gifts & Culture: Corporate gifts for holidays, birthdays, and a true team atmosphere where your voice always matters.
 

Our Perfect Match: 
1️⃣ Databricks Expertise: Strong hands-on experience with Databricks, general BI, data platform architecture, and advanced data modeling.
 2️⃣ SAP BW Context: solid background in SAP BW sufficient to analyze existing BW structures, models, and business logic for migration. 
3️⃣ Enterprise Migration: Proven track record in large-scale data migration/modernization projects (ideally leveraging LLM-powered code translation or migration tools). 
4️⃣ Cloud & Domain: Cloud experience with AWS (or comparable platforms); exposure to enterprise Finance domain processes is a big plus. 
5️⃣ Location & Communication: Based in EU countries with English proficiency at B2/C1 level for smooth enterprise stakeholder communication.
 

Project Details: 
⏳ Duration: Dec/Jan start until end of Q1 2028 (Full-time). 

About the Role:

We are looking for an experienced Senior Data Engineer to join our team and help build scalable, secure, and high-performance data platforms. In this role, you will work closely with Data Architects, Engineers, Analysts, DevOps specialists, and Data Scientists to design, develop, and optimize modern cloud-based data ecosystems.

This is a full-time remote position for a senior-level professional who can commit 40 hours per week and take ownership of complex data engineering initiatives.

🔹 Responsibilities:

As a Senior Data Engineer, you will:

* Collaborate with Data Architects on designing and implementing data solutions across Azure, AWS, or IBM Cloud environments

* Build, maintain, and optimize modern data ecosystems and data pipelines

* Develop and support data ingestion, transformation, and processing solutions

* Work closely with cross-functional teams, including Data Engineers, Analysts, DevOps Engineers, and Data Scientists

* Implement security best practices to ensure the reliability and protection of cloud infrastructure and data processes

* Apply modern engineering principles and methodologies to support business growth and innovation

* Identify opportunities to improve data quality, reliability, scalability, efficiency, and overall platform performance

* Optimize data solutions to balance performance, maintainability, and cost-effectiveness

* Design and execute unit, system, and integration testing strategies

* Contribute to continuous improvement initiatives and engineering best practices

🔹 Requirements:

* Strong commercial experience as a Data Engineer

* Advanced proficiency in Python for data processing, transformation, and analysis

* Strong expertise in SQL, including query optimization and database performance tuning

* Hands-on experience with Azure and/or AWS data platforms and services

* Experience designing and maintaining scalable cloud-based data solutions

* Solid understanding of data engineering best practices, data modeling, and ETL/ELT processes

* Experience with software development lifecycle methodologies and Agile environments

Nice to Have:

* Experience with IBM Cloud data services

* Knowledge of data governance and cloud security practices

* Experience working in enterprise-scale data environments

🌍 What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

We are seeking a skilled ML/AI Engineer to join our team and deliver cutting-edge ML/AI models in the ASR domain and legal insights more broadly. The core of this role is building, deploying, and serving ML models in production. 

A key part of this role is speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. Experience with LLM-based solutions and agentic flows is an advantage, not a requirement. 

What you’ll do: 

• Build, deploy, and serve ML models in production — the core of the role — optimizing inference performance, latency, and efficient GPU utilization. 
• Support and extend our speech solutions, including 3rd-party ASR integrations and self-hosted ML models. 
• Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER. 
• Secondary: Integrate LLMs and agentic flows into production solutions where they add value, including fine-tuning existing models. 

What you’ll bring: 

Core (required): 

• Solid background in machine/deep learning, with 4+ years of experience. 
• Strong Python skills and experience working in Linux environments. 
• Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow) and training workflows. 
• Experience with MLOps pipelines and serving/deploying models in production. 
• Experience optimizing models for inference, including GPU acceleration. 
• Experience with Docker, gRPC, and serverless / micro-services architectures on cloud infrastructure (AWS/GCP/Azure). 
• Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions). 

Nice to have (secondary / optional): 

• Experience building and productizing agentic flows and AI-driven solutions (1+ year). 
• Familiarity with LLM / agent orchestration frameworks such as CrewAI, AWS Bedrock, Temporal, AgentCore, or LiteLLM. 
• Prior ASR / speech experience — not required; willingness to learn this domain is what matters most. 

Dash Financial Technologies is a leading trading technology provider to the institutional trading community. With a suite of highly customizable tools, Dash designs and delivers intelligent, high performance solutions in four product categories: Trading Technologies, Execution Services, Analytics and Regulatory Technologies. With a relentless focus on transparency, performance and customization, Dash Financial Technologies caters to institutions that require increasingly specialized, complex and adaptable tools to exceed their goals surrounding best execution

We are looking for a skilled Business Analyst, ideally with experience in Capital Markets domain, as a ramp-up of our BA capacity on a modern order management system project. 

 

Requirements
o You have a technical background
o You have a passion for great, structured documentation and the benefits of knowledge management.
o You communicate clearly and precisely, leading others and transferring knowledge efficiently.
o You form strong, honest, and mutually respectful relationships with the key stakeholders

Desirable
o You have experience working with asset classes such as US Equities and Equity/Index Options.
o You have a good understanding of order management specifics particularly in the trading systems
o You are familiar with the FIX Protocol

Responsibilities
o Play the role of Business/System Analyst
o Work closely with the client to ensure requirements are captured, the scope is controlled, and expectations are met
o Work closely with the development team to do the entire system design
o Participate and facilitate workshops, stakeholder interviews, UX design sessions, solution planning & review meeting, etc.
o Specification of new functionality across the frontend and backend components
o Ongoing improvement of knowledge through better documentation and knowledge management infrastructure
o Play a proactive role in proposing new processes, tools & approaches
o Assist in project planning, quality control, and user acceptance testing
o Help investigate complex functional software issues, assist in root cause analysis, and establish a solution
o Identify and manage risks and flag major issues early

We are offering You 

• Remote work   
• Flexible working hours 
• All necessary equipment (laptop,monitors. etc.) 

We’re looking for a Data Engineer to improve our data infrastructure and integration workflows.

This role is a great fit for someone who can quickly step into an existing environment, bring strong technical expertise, and help us build reliable, scalable solutions with a practical hands-on approach.

Responsibility:

• Design and build data templates for integration workflows
• Optimize and improve existing data pipelines
• Ensure smooth and reliable integration across SaaS systems

Requements:

• Commercial experience as a Data Engineer
• Python skills for data engineering tasks
• Understanding of building efficient, scalable, and maintainable data pipelines

Would be a plus:

• Experience with ETL / ELT

• Experience with cloud-based data platforms and modern data stack

   

Required languages

EnglishB2 - Upper Intermediate

We are seeking a hands-on Senior DevSecOps Engineer with strong AWS and Azure experience to embed security directly into our engineering lifecycle. In this role, you will be the technical engine that automates compliance guardrails, integrates security tooling (SAST/DAST, EDR, Vulnerability Management) into CI/CD pipelines, and routes critical security telemetry to our SIEM. Your mission is to build the automated scaffolding that allows software delivery to move at high speed without compromising on enterprise security or governance.

Key Responsibilities

·  CI/CD Security Automation: Design, build, and maintain secure deployment pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI). Integrate automated vulnerability scanning, secret detection, and software supply chain security (SCA) seamlessly into the developer workflow.

·  Policy-as-Code & Guardrails: Write, test, and deploy automated policy guardrails using Infrastructure as Code (IaC) linting and scanning tools (e.g., Checkov, Tfsec, OPA/Rego) to catch misconfigurations before they reach production.

·  Security Product Deployment: Automate the baking of EDR agents, vulnerability scanners, and monitoring tools into base machine images (AMIs, Azure Golden Images) and containerized base environments.

·  Vulnerability & Remediation Pipelines: Operationalize vulnerability management by building automated workflows that ingest findings from cloud security tools, prioritize them based on risk, and route them to engineering backlogs (e.g., Jira tracking).

·  Logging & SIEM Integration: Configure and automate the pipeline delivery of application, container, and infrastructure logs to central logging repositories and SIEM systems for real-time threat hunting.

·  Developer Enablement: Serve as a bridge between Security and Engineering, providing developer-friendly remediation guidance and creating reusable, secure-by-default code templates (Terraform modules, Helm charts).

Required Skills & Qualifications

·  DevSecOps & CI/CD Pipelines: Deep, practical experience constructing and securing automated build/release pipelines at scale.

·  Multi-Cloud Platforms: Hands-on engineering experience configuring native security services and access controls in both AWS and Azure.

·  Infrastructure as Code (IaC): Advanced proficiency with Terraform or cloud-native tooling (Bicep, CloudFormation), focusing on modular design and immutable infrastructure.

·  Security Tooling Implementation: Direct experience implementing and maintaining security products across the lifecycle (e.g., SonarQube, Prisma Cloud, Wiz, Snyk, CrowdStrike, or Sentinel).

·  Container & Orchestration Security: Strong understanding of Kubernetes (EKS/AKS) security best practices, service meshes, and container runtime defense.

Preferred Certifications

·  Certified DevSecOps Professional (CDP) or Practical DevSecOps certification

·  AWS Certified Security – Specialty or Azure Security Engineer Associate

·  Certified Kubernetes Administrator (CKA) / Certified Kubernetes Security Specialist (CKS)...

Description

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.

The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.

The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.

OU’s: Currently, Nuero, Cardio, Diabetes is the OU that HDP data platform is working with, but there could be more OU’s coming up with requirements in future.

GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements

As a System Engineer within the Company Research & Systems Engineering team, you will have the opportunity to work on cloud-based solutions with a strong focus on AWS, Data Engineering, and scalable data platforms. You will collaborate with cross-functional engineering teams to design, develop, integrate, and maintain reliable cloud-native systems and data workflows.

In this role, you will contribute to building and evolving AWS-based architectures, data processing pipelines, and integrations across distributed systems. You will develop a strong understanding of end-to-end system architecture, data flows, infrastructure, and operational requirements, helping to drive technical implementation and delivery throughout the software development lifecycle.

You will work closely with software engineers, data engineers, architects, and other stakeholders to ensure that solutions are scalable, secure, maintainable, and aligned with both technical and business requirements.

• 3+ years of experience in System Engineering, Software Engineering, Cloud Engineering, Data Engineering, or a related technical role.
• Strong software development experience with Python.
• Hands-on experience designing, developing, or supporting solutions on AWS.
• Experience with data engineering concepts and technologies, including data ingestion, ETL/ELT, transformation, validation, and data processing pipelines.
• Strong SQL skills and experience working with relational and/or NoSQL databases.
• Experience with REST APIs, service integrations, and distributed application architectures.
• Understanding of cloud-native architecture principles and modern software development practices.
• Experience troubleshooting applications and distributed cloud systems and performing root cause analysis.
• Experience with Git and modern CI/CD development workflows.
• Strong analytical and problem-solving skills with the ability to understand complex systems and data flows.
• Ability to work effectively with software, data, cloud, and machine learning engineering teams.
• BA/BS in Computer Science, Software Engineering, Information Technology, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience with AWS data services such as S3, Glue, Athena, EMR, or similar technologies.
• Experience with Amazon SageMaker and machine learning development or deployment workflows.
• Experience with Infrastructure as Code using AWS CloudFormation, Terraform, or AWS CDK.
• Experience with AWS monitoring and observability services such as CloudWatch and CloudTrail.
• Experience working in Agile/Scrum development environments.

Job responsibilities

• Work with engineering and cross-functional stakeholders to gather, analyze, clarify, and document business, functional, and non-functional requirements, translating them into clear system and technical requirements.
• Define system requirements, interfaces, data flows, integration requirements, acceptance criteria, and technical constraints for cloud-based software components, data platforms, and integrations.
• Maintain requirements throughout the development lifecycle, ensuring traceability between business needs, system requirements, technical design, implementation, and validation.
• Identify gaps, dependencies, assumptions, and potential technical risks in requirements and work with stakeholders to resolve them before and during implementation.
• Design and contribute to scalable AWS-based architectures supporting data ingestion, processing, transformation, storage, and distribution.
• Analyze data and system behavior to support architecture, implementation, performance, and product decisions.
• Collaborate with Data Engineering, Software Engineering, Cloud Engineering, DevOps, and Architecture teams to design and integrate end-to-end cloud solutions.
• Support operational monitoring, logging, alerting, and troubleshooting of cloud applications and data processing workflows.
• Contribute to system architecture and technical design discussions, including scalability, reliability, security, performance, and cost considerations.
• Participate in technical and requirements reviews to ensure solutions meet defined requirements, engineering standards, cloud best practices, and established software development processes.
• Support continuous improvement of cloud infrastructure, data pipelines, deployment processes, requirements management, and engineering practices throughout the software development lifecycle.

Playtika is looking for a Data Scientist Expert — Production ML to join the Data & AI department

In this position you will join a multidisciplinary team focused on personalization using Reinforcement Learning methods. Over the last few years, we have built a real-time recommendation engine based on Bayesian Multi-Armed Bandits — including our open-source PyBandits library — serving millions of players across multiple studios and use-cases.

This is an applied research role, with impact measured in production. Your primary contribution will be advancing the mathematical and statistical foundations of our existing solutions: identifying limitations, deriving principled improvements, and owning those improvements all the way through to production. You will not be handed research problems from above — you will find them yourself, inside systems that are already running at scale.

Scaling here is fundamentally a mathematical problem: identifying better statistical methods, proving they hold under real-world constraints, and knowing exactly how far they deviate from the ideal. That’s what sets this role apart.

Responsibilities

Identify mathematical and statistical limitations in existing ML solutions and deliver provably correct, more efficient alternatives
Validate the correctness of scaled solutions — diagnosing where distributed execution or approximation invalidates prototype-level results, and redesigning accordingly
Own the full lifecycle of your improvements: from research and prototyping through production deployment and impact measurement
Drive the evolution and scalability of our personalization and recommendation systems to meet future business and technical requirements
Contribute to end-to-end data-driven research including problem definition, data collection, model development, evaluation, and deployment
Collaborate with cross-functional teams (engineers, BI, Product) to deploy solutions quickly and effectively
Mentor Data Scientists and ML Engineers, and serve as a technical reference on statistical and mathematical rigor across the organization

Qualifications

M.Sc or PhD in Computer Science, Mathematics, Statistics, Engineering or a related field
5+ years of relevant working experience, including significant production ML ownership
Demonstrated experience taking statistically sophisticated models from prototype to production and operating them successfully under real-world business constraints.
Experience with neural network architectures, including the ability to diagnose, interpret and debug their behavior in probabilistic or decision-making contexts (e.g. Bayesian Neural Networks, Neural Linear models)

Strong theoretical foundation in at least one of: Multi-Armed Bandits, Bayesian methods, online learning, recommendation systems, or related decision-making frameworks
Strong understanding of experimentation, causal inference and statistical evaluation of online decision systems.
Strong hands-on Python engineering skills, with the ability to design, implement, review, and maintain production-quality code, leveraging modern AI coding assistants (e.g., Claude, Cursor) to improve productivity and code quality
Proficiency in SQL
Clear written and verbal communication — able to explain statistical reasoning to non-technical stakeholders
Ability to operate autonomously and influence decisions across teams without direct authority.

Nice to have

Experience with probabilistic programming frameworks (e.g. PyMC or Numpyro)
Familiarity with MLOps tooling (experiment tracking, model serving, monitoring)
Familiarity with approximate inference methods (variational inference, MCMC)
Experience with PySpark
Experience in the Mobile Gaming industry

Trinetix is looking for a skilled Business Analyst with strong expertise in SCRUM and a deep understanding of Agile delivery practices. This role involves close collaboration with product owners, stakeholders, and development teams to define, refine, and translate business needs into clear, actionable user stories and technical solutions. The ideal candidate is detail-oriented, proactive, and comfortable driving clarity and alignment across cross-functional teams. 
 

Requirements 

• 4+ years of experience in Business Analyst role 
• Strong knowledge of SCRUM methodology and practical experience working in Agile environments 
• Proven ability to work closely with product owners, stakeholders, and development teams 
• Experience in backlog refinement, defining acceptance criteria, and writing clear, actionable user stories 
• Ability to translate business needs into technical requirements 
• Strong communication and facilitation skills 
• Experience working with tools such as Azure DevOps, Microsoft Teams, Microsoft Excel, Confluence or SharePoint, Miro 
   

Nice-to-haves 

• Experience supporting or leading sprint planning 
• Background in business analysis or product ownership 
• Understanding of software development processes and technical terminology 
• Experience working in cross-functional, distributed teams 
• Familiarity with enterprise-level workflows or large-scale Agile environments 
   

Core Responsibilities 

• Collaborate with product owners, stakeholders, and development teams to define and refine business requirements 
• Lead and facilitate backlog refinement sessions to ensure user stories are well-defined, prioritized, and aligned with organizational goals 
• Support sprint planning by preparing clear, structured requirements and ensuring teams understand the scope 
• Ensure all user stories include clear acceptance criteria and are actionable for development teams 
• Translate business needs into effective technical solutions while fostering collaboration across teams 
• Maintain documentation and support alignment using tools such as Azure DevOps, Confluence/SharePoint, Miro, etc. 

Softsich is a young and ambitious international product tech company that develops scalable B2B digital platforms. We’re on the lookout for an experienced Data Engineer who’s ready to grow with us and shape high-load, data-driven solutions used by international partners.

It’s a match if you have:
– Hands-on experience with Python for data processing and pipeline development.
– Hands-on experience developing and maintaining data pipelines in Airflow.
– Experience with cloud platforms (AWS preferred).
– Strong SQL skills and experience with NoSQL databases (MongoDB).
– Experience with Git for version control and collaborative development workflows.
– Experience with CI/CD pipelines for building, testing, and deploying data pipelines and related code.
– Ability to work independently, take ownership, and collaborate effectively with analysts and product owners.
– Excellent collaboration skills.

Your key responsibilities will include:
– Develop and maintain data pipelines orchestrated with Airflow using Python-based DAGs.
– Develop and maintain data models in the analytical data warehouse (DWH) to support reporting and business intelligence use cases.
– Develop and maintain data validation scripts using Python, SQL, and pandas.
– Collaborate with analysts and product owners to deliver well-structured, reliable datasets.

Nice to have:
– Experience with DWH Snowflake.
– Experience with DataOps, DevOps practices and performance optimization.
– Experience with NoSQL databases (preferably MongoDB).

What we offer:

– Flexible schedule and remote format or offices in Warsaw/Kyiv — you choose.
– 24 paid vacation days, sick leaves, and health insurance (UA-based, other locations in progress).
– A supportive, friendly team where knowledge-sharing is part of the culture.
– Coverage for professional events and learning.
– Birthday greetings, team buildings, and warm human connection beyond work.
– Zero joules of energy to the aggressor state, its affiliated businesses, or partners.

Send over your CV now — we’d love to get to know you better!

Hi there! Our Magnetics team is currently looking for a Lead Data Analyst!  
🧲 About the role 

We are an iGaming product company creating global B2C solutions, driving business growth, and delivering products players love.
Our team of 100+ is in an active growth phase, expanding markets and creating new roles. The pace is fast, decisions matter, and you’ll work alongside people who truly know what they’re doing.

Our values
 

• Lead from Within: We grow through trust, support, and knowledge sharing. We invest in our people to shape future leaders from the inside.
• Growth Mindset: A drive to act, experiment, and learn from mistakes. We value initiative and fast decision-making over rigid processes.
• Product Ownership: Personal accountability for user impact. Every role shapes the final product, so we treat our work as our own.

As we continue to grow, we're looking for a Lead Data Analyst who sees analytics as a strategic business function rather than just reporting numbers. In this role, you'll partner closely with cross-functional teams to turn complex data into actionable insights, build scalable analytics solutions, and support data-informed decisions across acquisition, retention, and product growth.
We're looking for someone with a strong business and product mindset who is passionate about uncovering growth opportunities, improving how teams use data, and building analytics systems that make a measurable impact on business performance.

What we're looking for:

• At least 2 years of experience in a Lead Analytics role within a highly competitive digital business environment
• Deep understanding of business needs across different departments
• Strong understanding of acquisition and retention business requirements, as well as expertise in designing reports and dashboards tailored to a product-driven business
• Knowledge of organizing and implementing technical knowledge base solutions
• Ability to build multi-factor traffic ROI forecasting models
• Advanced proficiency in data analysis tools (Tableau, SQL, and other relevant analytics tools)
• Ability to ensure compliance with security requirements and best practices
• Experience in designing and implementing automated analytics systems
• Strong attention to detail and a systematic approach to work

What you'll do: 
 

• Develop high-quality analytical reports and dashboards based on a deep understanding of the business, departmental needs, and operational processes
• Ensure high standards of report design, usability, and data presentation
• Effectively utilize Tableau, SQL, and other tools for data collection, processing, and analysis
• Automate reporting processes to improve efficiency, accuracy, and timeliness of insights
• Collaborate with cross-functional teams to gather requirements, share insights, and support the
  achievement of common business goals

🧲 What we offer:

• Flexible work format. Remote, hybrid or office: your choice.
• Flexible working hours.
• 20 days of paid vacation.
• Regular salary reviews.
• Health insurance.
• Learning and development. Corporate courses, workshops and platform access: all company-funded.
• Team building and events. Online and offline, because great products are built by people who trust each other.
  
  Last but not least, we value honesty over bureaucracy. We practice clear, two-way feedback and structured quarterly performance reviews, ensuring your efforts are recognised and your professional growth is fully supported.

Are you the ultimate talent magnet? Show us your CV and let's make it a match!