Responsibilities:

• Design and build end-to-end ML pipelines covering feature engineering, model training, backtesting, validation, reporting, and batch inference.
• Convert data science prototypes into reliable and maintainable production solutions.
• Develop a configurable ML framework using reusable components and parameter-driven workflows.
• Build and maintain Python-based ML workflows using an existing codebase.
• Support data preparation and transformation workflows in Snowflake and dbt Cloud.
• Implement data quality checks, automated testing, versioning, monitoring, and CI/CD.
• Integrate model outputs into downstream business systems and operational workflows.
• Contribute to architecture decisions and propose practical implementation approaches.
• Support production operations, troubleshooting, model refreshes, and continuous improvement.
• Collaborate with data scientists, data engineers, architects, and business stakeholders.

What we expect:

• 6–8 years of experience in machine learning engineering, software engineering, data engineering, or a related field.
• Strong Python software engineering skills, including experience with reusable and object-oriented code.
• Experience building production ML pipelines.
• Hands-on experience with traditional ML methods and libs (pandas, NumPy, scikit-learn, PyTorch).
• Hands-on experience with Docker.
• Strong SQL and data engineering skills.
• Practical experience with Snowflake and dbt Cloud.
• Experience working with AWS.
• Experience with Git-based CI/CD workflows, such as GitHub Actions.
• Understanding of testing, monitoring, versioning, reproducibility, and production support.
• Strong communication, ownership, troubleshooting, and problem-solving skills.

Nice to have:

• Experience with scheduled batch prediction pipelines.
• Experience building configurable frameworks that support multiple products or business units.
• Familiarity with CRM or other downstream business-system integrations.
• Familiarity with Kubernetes, workflow orchestration, or infrastructure as code.
• Exposure to generative AI or LLM-based applications.
• Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments.

Responsibilities:

• Develop predictive models that generate insights, recommendations, and business signals.
• Perform data discovery, exploratory data analysis, feature engineering, and feature selection.
• Build classification, regression, clustering, segmentation, recommendation, and forecasting models.
• Design and execute model validation, experimentation, and backtesting methodologies.
• Evaluate model performance and translate results into clear business recommendations.
• Develop reusable modeling frameworks and reproducible Python workflows.
• Work with data stored in Snowflake and transformations developed in dbt Cloud.
• Partner with ML engineers to containerize, deploy, monitor, and improve models in production.
• Support model retraining, performance monitoring, and continuous improvement.
• Translate business questions into analytical hypotheses, measurable objectives, and practical solutions.
• Communicate findings, assumptions, risks, and business implications to technical and non-technical stakeholders.
• Collaborate with data engineers, ML engineers, product teams, and business stakeholders.

What we expect:

• 6–8 years of experience in data science, applied machine learning, statistics, or a related field.
• Strong Python and SQL skills.
• Hands-on experience with traditional ML methods and libs (pandas, numpy, scikit-learn, pytorch).
• Strong knowledge of predictive modeling, statistical analysis, experimentation, and model evaluation.
• Experience designing validation and backtesting frameworks.
• Practical experience with Snowflake and cloud-based analytics platforms.
• Experience taking models from experimentation through production deployment.
• Familiarity with Docker, data engineering concepts, and MLOps practices.
• Strong analytical thinking, communication, stakeholder management, and problem-solving skills.

Nice to have:

• Experience developing models that generate customer-level insights or recommendations.
• Familiarity with AWS and dbt Cloud.
• Knowledge of causal inference, experimentation, or optimization methods.
• Exposure to generative AI, LLM-based applications, graph analytics, or RAG.
• Experience in pharmaceutical, biotechnology, healthcare, or life sciences environments.

Design and produce a comprehensive Low Level Design (LLD) for the target Microsoft 365 environment.

Plan and deliver an end-to-end Microsoft 365 tenant-to-tenant migration.•Build and configure a new Microsoft 365 tenant.

Migrate workloads including: Microsoft 365 users Groups and Teams SharePoint Intune-managed devices

Configure and validate: Conditional Access Multi-Factor Authentication (MFA) Intune Configuration & Compliance Policies Role-Based Access Control (RBAC)

Job Specification for Microsoft365 Tenant Migration pg.

2oEnterprise Applications and Single Sign-On (SSO) Data Loss Prevention (DLP)

Produce migration plans, run books and communication plans.

Review licensing and recommend the most appropriate Microsoft licensing model.

Troubleshoot migration issues and provide post-migration support.

Produce comprehensive handover and operational documentation.

Manage project delivery, timelines, dependencies and stakeholder communications throughout the engagement.

Proven experience delivering end-to-end Microsoft 365 tenant-to-tenant migrations.

Strong experience producing Low Level Design (LLD)documentation for Microsoft 365 environments.

Excellent Microsoft 365 administration experience, including: Entra ID (Azure AD)

Exchange Online SharePoint Online Microsoft Teams , Conditional Access Microsoft Defender

Experience configuring Identity, Security and Compliance services.

Strong understanding of Microsoft licensing.

Experience using migration tools (e.g. Bit Titan Migration Wiz or similar).

Demonstrable project management experience, including planning, risk management, stakeholder management and delivery coordination.

Job Specification for Microsoft365 Tenant Migration pg. 3

Excellent technical documentation skills, including design documents, migration run books, implementation guides and handover documentation.

Strong troubleshooting and problem-solving abilities.

Excellent communication skills with both technical and non-technical stakeholders.

Must-Have Experience:

Low Level Design (LLD)

End-to-end Microsoft 365 tenant migration delivery

Project management

Technical documentation

Migration planning and execution

Stakeholder engagement Desirable

Microsoft certifications (Microsoft 365, Azure or Security).

Experience delivering large-scale enterprise migrations.

Experience working within regulated environments.

Knowledge of Microsoft security and compliance best practices.

Experience in manual testing of web applications for at least 2 years. Ability to write test cases and bug reports according to the standard (reproduction steps / expected / actual result / severity). Working with Swagger/OpenAPI, testing experience through Postman/Insomnia. Understanding client-server architecture and JWT authorization at a basic level. Experience in testing B2B/enterprise SaaS platforms. Fluent in Russian. Plus: experience in logistics/transportation, testing PDF/DOC document generation, basic SQL, experience working with Docker environments.  

What skills are important to us?

English at the B1 level or higher.

Willingness to fully immerse yourself in learning and work – 40 hours a week.

Accommodation in Almaty

What skills are important to us?

English at the B1 level or higher.

Willingness to fully immerse yourself in learning and work – 40 hours a week.

Accommodation in Astana

If you:

• You have an unconventional mindset, always trying to make everything even better than it is now.;
• They participated in Olympiads of various sizes in natural sciences;
• A friendly and dedicated team player;
• Making the right decisions in critical situations;
• Be responsible about deadlines;
• Be honest with yourself and others;
• Multitasking and stubborn;
• You want to study in the strongest team.

You should know:

• Basics of HTML&CSS Programming;
• Basic understanding of javascript;
• The theory of how large systems work;
• How to change the values of two variables without using the third variable;
• Have basic knowledge of Mongo DB, Node JS
• Knowledge of Figma, photoshop, coloristics, typography, illustration, graphic designer skills, have your own style and taste (in the direction of a web designer);

Requirements

• Product Manager experience of at least 2 years (preferably in SaaS, Web or Mobile).
• Understanding Agile/Scrum/Kanban.
• Ability to describe business requirements and functional requirements.
• Experience writing User Stories, Use Cases, Acceptance Criteria.
• Task prioritization skills (MoSCoW, RICE, Kano, ICE).
• Experience working with Jira, Confluence, Notion or their analogues.
• Basic understanding of UX/UI.
• Knowledge of the software development lifecycle (SDLC).
• Analytical thinking.
• Communication and presentation skills.
• Experience working with product metrics will be an advantage.

That would be a plus

• Experience working with AI products.
• Knowledge of SQL.
• Understanding the REST API.
• Experience of integration with external services.
• Experience working with Figma.
• Knowledge of the basics of Data Analytics (GA4, Amplitude, Mixpanel, etc.).

• work experience of at least 1 year as a business or system analyst with software in finance, accounting, banking software;
• knowledge in the field of banking business, banking accounting;
• work experience as a technologist/analyst of banking products, knowledge of the bank's business processes is desirable.;
• knowledge and experience in using methods for developing system requirements, methods of system analysis, standards and tools for describing business processes;
• knowledge of the IBSO product (IBSO)

design, development and configuration of IBSO systems functionality

• work experience as a programmer in the financial sector
• understanding the bank's business structure and banking processes
• knowledge of the basics of banking and accounting is desirable
• knowledge of ORACLE database architecture and PL/SQL language, PL+
• consider candidates with experience working with other DBMS
• team and project work experience;
• willingness to travel.