Jobs Data Science

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers, with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production, agricultural business, parcel delivery, logistics and banking.
 

The Foodtech team is looking for a Data Scientist to develop the Operational Analytics function for a fast growing food delivery business. In this role, you will focus on time series forecasting, regression modeling, simulation modeling, and end-to-end machine learning pipelines to support resource planning and operational decision-making.

You will be responsible for developing simulation-based models that serve as a foundation for a digital twin of operational processes, enabling scenario analysis, stress testing, and what-if simulations for capacity planning and operational optimization.

You will work closely with product, engineering, and operations teams to transform data into measurable business impact through production-ready ML and simulation solutions.
 

Job Responsibilities:

• Develop and implement time series forecasting models for resource planning (demand, capacity, couriers, delivery slots, operational load);
• Build regression and machine learning models to explain key drivers and support operational decisions;
• Apply a wide range of time series approaches from classical models (SARIMA, ETS, Prophet) and ML models (GB) to modern Deep Learning models (LSTM, Temporal CNNs, Transformers for TS);
• Design, build, and maintain end-to-end automated ML pipelines, deploy and operate models in production using AWS SageMaker;
• Orchestrate training and inference workflows with Apache Airflow;
• Analyze large-scale operational datasets and convert results into insights, forecasts, and actionable recommendations;
• Collaborate with product managers, engineers, and operations teams to define business problems and validate analytical solutions;
• Monitor model performance, forecast stability, and business impact over time.
   

Requirements:

• Bachelor’s Degree in Mathematics / Engineering / Computer Sciences / Quantitative Economics / Econometrics;
• Strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;
• At least 2 years working experience on Data Science;
• Experience of the full cycle of model implementation (data collection, model training and evaluation, model deployment and monitoring);
• Ability to work independently, proactively, and to decompose complex problems into actionable tasks.
   

Skills:

• Strong proficiency in Python with solid application of object-oriented programming (OOP) principles (modular design, reusable components, maintainable code);
• Solid experience in time series forecasting and regression modeling;
• Practical knowledge of:o Classical and ML forecasting techniques;
  o Statistical methods (hypothesis testing, confidence intervals, A/B testing);
• Advanced SQL skills (window functions, complex queries);
• Experience building automated ML pipelines;
• Understanding of MLOps principles (model versioning, monitoring, CI/CD for ML).
   

Nice to have:

• Hands-on experience with AWS SageMaker (training jobs, endpoints, model registry);
• Experience with Apache Airflow for data and ML workflow orchestration;
• Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau);
• Experience working with large-scale production data systems.
   

What We Offer:

• Competitive salary;
• Professional & personal development opportunities;
• Being part of dynamic team of young & ambitious professionals;
• Corporate discounts for sport clubs and language courses;
• Medical insurance package.

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

Our platform is a cloud-based AI-driven workspace that automates statistical analysis validation and generation for clinical research. It serves large pharmaceutical and biotech clients by extracting, validating, and producing complex tabular outputs and regulatory deliverables. 

The system handles high volumes of hierarchical tables, figures and listings, applying both classical and generative NLP to accelerate review cycles, reduce manual double-programming and maintain a full audit trail. 

About the Role:

As a Middle Data Scientist, you will support the development of novel AI and algorithmic approaches—particularly in NLP and tabular data—to enhance our core platform. You will take hypotheses through proof-of-concept, explore complex clinical datasets, identify patterns, evaluate alternative methods, and recommend optimal solutions. 

Key Responsibilities:

• Design, develop, and prototype NLP algorithms (classical and generative) for document parsing, NER, classification, and table generation

• Implement tabular data models and pipelines for metadata extraction, transformation, and validation

• Work with large, heterogeneous clinical datasets: clean, preprocess, and structure data for analysis

• Evaluate multiple algorithmic approaches, benchmark performance, and select optimal solutions

• Maintain reproducible code, thorough documentation, and version control for research assets

Required Competence and Skills:

• 2- 4 years of industry experience in NLP and/or tabular data processing
• 1+ years of hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
• Proven track record of delivering AI-driven projects into production
• Expertise in classical NLP techniques and generative methods (e.g., text-to-SQL, generative tabular models)
• Strong proficiency in Python and associated data science libraries
• M.S. or Ph.D. in Computer Science, Data Science, Statistics, or related quantitative field
• Excellent English communication skills, both written and verbal

Nice to Have:

• Experience with cloud-based NLP platforms or managed AI services

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

Our Customer:

Our customer is a global, data-driven digital advertising technology company operating at large scale across mobile apps and web platforms.
 

Your Tasks:

• Analyze large, complex datasets to uncover patterns, insights, and business opportunities;
• Design, build, and own scalable, end-to-end data pipelines;
• Develop and productionize advanced machine learning models and algorithms, particularly in monetization-related domains;
• Build and maintain data models for real-time (online) processing;
• Contribute to the creation of new data-driven products and continuously improve existing ones;
• Collaborate with Product, BI, Analytics, DevOps, R&D, and Marketing teams to deliver complete solutions;
• Lead full production releases, including requirements analysis, testing, monitoring, result evaluation, and rapid response to critical issues.
   

Required Experience and Skills:

• 6+ years of experience as a Data Scientist with a strong foundation in machine learning concepts and models;
• Previous experience in the Ad-Tech industry;
• Hands-on experience working on large-scale, high-load systems processing billions of requests per second;
• Hands-on experience with Python including writing production-ready code and working with modern Python frameworks and tooling;
• Experience with data science / ML libraries and models, such as regression and classification models (e.g. XGBoost, LightGBM), recommendation systems, and related ML techniques;
• Solid understanding of databases and SQL for data analysis and retrieval;
• Experience with monitoring and alerting tools such as Grafana and Kibana;
• Proven experience working in real-time / online environments;
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field;
• Strong end-to-end ownership mindset: ability to take solutions from research and experimentation through implementation and production;
• Fluent English with strong communication and collaboration skills.
   

Would Be a Plus:

• Familiarity with the programmatic advertising ecosystem (DSPs, SSPs, ad exchanges);
• Experience with relational databases (e.g. Vertica, VoltDB) and non-relational databases (e.g. MongoDB);
• Experience working with PMML.

Working conditions

5-day working week, 8-hour working day;

Remote work.

Role summary
We are looking for a Senior Data Scientist to build the core intelligence layer of our Session Analyzer product: scoring, audience segmentation, and prescriptive recommendations for pharmaceutical marketing teams. You will operate as a “full-stack” data scientist across data validation, data engineering (prod pipelines), ML modeling, causal measurement, and AI-assisted workflows (agents for insights and data diagnostics). You will work directly with the Product Lead and Tech Lead.
 

What you will do

• Design and ship scoring, segmentation, and recommendation features based on pixel session/event data, NPI-enriched profiles, and 3rd-party datasets.
• Build a data quality & validation framework from scratch: tests, monitors, anomaly detection, drift tracking, and root-cause workflows across the data chain.
• Deliver batch PoC (days latency) and evolve to near-real-time MVP (hours latency) pipelines and feature tables.
• Develop and evaluate ML models for engagement prediction and audience targeting; ensure calibration, stability, and business-relevant lift.
• Define and implement measurement/attribution approaches to support ROI uplift and explain “what worked / why”.
• Build AI agents for (1) automated data issue diagnostics and (2) insight/presentation generation, with guardrails and traceability.
• Produce outputs as score tables, top insights, aggregates/features, dashboards/reports, and APIs for audience activation and CDP/CRM integrations.

Success metrics

• Improved Engagement score
• Measurable uplift in campaign ROI
• Reduced time-to-insight
• Increased share of HCPs with actionable recommendations
• Improved coverage/quality signals (e.g., NPI resolve rate progress, event capture reliability)

Requirements (must-have)

• 5+ years in Data Science / Analytics roles with production ownership.
• Strong Python + SQL; hands-on building production pipelines and data products.
• Experience with event/session analytics, aggregation modeling, and working with noisy web/pixel data.
• Proven ability to build propensity/engagement models, segmentation, and recommendation logic; strong evaluation practices.
• Working knowledge of causal inference / attribution methods for marketing effectiveness.
• Experience with GCP / BigQuery in production; familiarity with ClickHouse/Postgres is a plus.
• Ability to operate end-to-end: problem framing → data validation → modeling → deployment → monitoring → stakeholder comms.
• Hands-on experience building and operating data-driven marketing/advertising analytics products, including event-level measurement, audience segmentation, activation workflows, and performance attribution (AdTech/MarTech environments).

Nice-to-have

• Experience with agents (LLM-based workflows), automated insights, and safe deployment patterns.
• Familiarity with data quality tooling (e.g., Great Expectations/dbt tests) and observability.

Soft skills & values (required)
Openness

• Direct feedback, acknowledges mistakes, listens and acts on critique.

Internal Locus

• Takes responsibility for outcomes, analyzes own decisions first, learns quickly from failures.

Get it done

• Delivers end-to-end, removes blockers independently, completes work to production-grade finish.

Self-improvement

• Continuously adopts new tools (incl. AI), improves workflows, increases productivity without heavy training overhead.

Ownership

• Treats the product and system results as their responsibility, not just personal tasks/KPIs; minimizes need for micromanagement.

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

Our platform is a cloud-based AI-driven workspace that automates statistical analysis validation and generation for clinical research. It serves large pharmaceutical and biotech clients by extracting, validating, and producing complex tabular outputs and regulatory deliverables. 

The system handles high volumes of hierarchical tables, figures and listings, applying both classical and generative NLP to accelerate review cycles, reduce manual double-programming and maintain a full audit trail. 

About the Role:

As a Strong Data Scientist you will own the end-to-end development of novel AI and algorithmic solutions that power our core platform. You will translate research hypotheses into proofs of concept, select and benchmark advanced NLP and tabular-data techniques, and collaborate with engineering teams to integrate your work into production. 

Key Responsibilities:

• Define and drive the AI research roadmap, mentoring peers on practical implementation.
• Design, develop and evaluate NLP and tabular-data algorithms using GenAI, retrieval-augmented generation (RAG), deep learning, classical ML, NER and rule-based methods.
• Explore large clinical datasets, perform data cleaning and feature engineering for downstream model training.
• Build and maintain data pipelines for extraction, transformation and preprocessing of structured and semi-structured inputs.
• Stay current on state-of-the-art techniques in NLP, generative AI and tabular-data analysis, and integrate best practices.
• Collaborate with cross-functional teams, including software developers, DevOps engineers to integrate the research solutions into production. 

Required Competence and Skills:

• 3+ years of industry experience in NLP and/or tabular-data processing within a production setting.
• 2+ years of hands-on experience with deep learning methods and frameworks (e.g., PyTorch, TensorFlow).
• Expertise in both classical NLP (tokenization, NER, parsing, rule-based) and generative NLP (text-to-SQL, table generation, RAG).
• Advanced Python programming skills and familiarity with data science libraries (pandas, scikit-learn).
• Proven track record of delivering AI-driven projects into production environments.
• M.S. or Ph.D. in Computer Science, Machine Learning or a related quantitative field.
• Strong written and verbal communication in English.
• Excellent collaboration, interpersonal skills and ability to work independently with minimal oversight.

Nice to Have:

• Familiarity with cloud-based NLP platforms and MLOps tooling.
• Experience with large-scale table analytics or regulatory statistical outputs.

Location: Remote / Hybrid
Employment: Full-time

About the Role

We are looking for a Senior AI / Data Scientist to design, build, and deploy machine learning solutions in a production environment. You will work across the full data lifecycle — from exploration to scalable deployment.

Responsibilities

• Develop and deploy machine learning models
• Analyze and process large datasets
• Build and maintain end-to-end ML pipelines
• Optimize models and business metrics
• Collaborate with product and engineering teams

Requirements

• 4+ years of experience in Data Science / ML / AI
• Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch / TensorFlow)
• Experience deploying models to production
• Solid SQL and data handling skills
• Strong understanding of statistics and A/B testing

Nice to Have

• Experience with NLP / Computer Vision / LLMs
• Familiarity with MLOps tools (Docker, MLflow, CI/CD)
• Experience with cloud platforms (AWS / GCP / Azure)

What We Offer

• Competitive salary
• Flexible work format (remote/hybrid)
• Opportunity to work on cutting-edge AI projects

About the Project

Our client is one of the world’s largest professional services networks, delivering audit, consulting, tax, and advisory services to a majority of Fortune 500 companies, leading financial institutions, and rapidly growing enterprises.

The project is currently in an early phase, with more details to follow. The primary focus will be on designing and scaling modern data platforms within a cloud-based environment.

⸻

Role Overview

We are looking for a Data Architect with strong expertise in Azure and Databricks to design robust, scalable, and high-performance data architectures for enterprise-level solutions.

⸻

Key Responsibilities
• Design end-to-end data architecture and data platforms
• Define data models, standards, and best practices
• Work with Azure ecosystem (including Databricks)
• Collaborate with engineering teams to implement scalable solutions
• Ensure performance, reliability, and security of data systems
• Provide architectural guidance across multiple data initiatives
• Work closely with stakeholders to align technical solutions with business needs

⸻

Requirements (Must-have)
• 9+ years of experience in data / software engineering
• Strong experience in data architecture design
• Hands-on experience with Azure
• Solid experience with Databricks
• Strong background in data engineering / big data solutions
• Experience designing scalable data platforms
• English level C1+

⸻

Nice to Have
• Experience in enterprise or consulting environments
• Experience with large-scale distributed systems
• Background in regulated industries (finance, etc.)

⸻

What We Offer
• Fully remote work
• Opportunity to work with top-tier global clients
• Influence on architecture and strategic decisions
• Long-term engagement

Our Client is a cybersecurity software company that specializes in network and cloud security policy management and automation. It's platform helps large enterprises visualize, automate, and enforce consistent security policies across complex hybrid environments — including firewalls, cloud services, SASE, SD-WAN, and microsegmentation — while ensuring compliance and reducing risk.

Position Description:

This role combines excellent technical skills, driving multidisciplinary Data Science initiatives within complex, security policy management systems. The role drives the development of innovative, production-grade AI capabilities - including security AI agents and advanced machine learning models built on complex security data. Original thinking, deep technical rigor, intellectual agility, and exceptional problem-solving are essential.

Key Responsibilities

• Develop Data Science initiatives from problem definition through validation, production deployment, and monitoring of AI systems
• Develop security-focused AI agents and reasoning systems
• Develop advanced ML capabilities, including predictive modeling, anomaly detection, and classification
• Adapt and fine-tune LLM technologies for domain-specific security use cases

Position Requirements:

• M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline
• At least 3 years of hands-on Data Science experience, delivering end-to-end solutions into production environments
• Deep understanding of machine learning theory and practical model behavior
• Expertise in Python and the modern Data Science ecosystem (NumPy, Pandas, Scikit-learn, PyTorch / TensorFlow, etc.)
• Solid understanding of LLM architectures and fine-tuning methodologies
• Excellent interpersonal skills and proven ability to work within multidisciplinary product teams
• Strong analytical rigor and structured problem-solving capability

We are looking for a Middle/Senior Machine Learning Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions.

Key Responsibilities:

• Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.
• Build AI and ML solutions within Palantir Foundry, using Python and existing Foundry pipelines, Ontology objects, and workflows.
• Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases.
• Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.
• Conduct experiments, evaluate model performance, and iterate on features and model approaches.
• Integrate AI models into Foundry workflows to surface insights and support business processes.
• Support model deployment and monitoring by following established team standards and best practices.
• Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.
• Document model behavior, assumptions, and limitations to support transparency and compliance.
• Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members.

Requirements:

• 3+ years of experience in machine learning, AI engineering, or applied data science.
• Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization).
• Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.
• Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.
• Familiarity with enterprise data environments and collaborative development workflows.
• Ability to clearly explain model results and AI behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to have: 

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.

Skills requirements:
• Strong Python Experience (1 year +);
• Experience with LLM , Diffusion models (1 year +);
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

Key responsibilities:
• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications;

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary nominated in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

We are looking for a Computer Vision Engineer with solid ML/DL experience to join our team on challenging projects.
We consider engineers at Middle and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications:

• 3+ years of experience in computer vision
• High proficiency in Python
• Strong experience with deep learning and the PyTorch framework for computer vision tasks
• Research experience in computer vision with a focus on delivering results
• Ability to work independently or within a small team, with a strong sense of ownership over results

Nice to Have:

• Experience with deep learning solutions for detection, tracking, image retrieval, and segmentation tasks
• Understanding of geometric computer vision principles
• Model optimization: quantization, pruning, neural network compilers
• Hands-on experience implementing low-level CV algorithms
• Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
• Knowledge of C++

About Keymakr

• Keymakr specializes in end-to-end dataset preparation, including video and image annotation and labeling for AI projects.
  We take a personalized approach, delivering customized solutions tailored to each client’s needs.
   
• Our strong in-house R&D team develops and adapts annotation tools for every client, allowing us to successfully handle even the most complex requirements.

About the Role:

• We are looking for a Data Management Specialist to manage, process, and maintain large volumes of data and media assets used in AI and technology projects.
   
• This role focuses on ensuring data integrity, consistency, and availability while optimizing workflows through automation and close collaboration with cross-functional teams.
   

Key Responsibilities:

1. Manage and manipulate data using Linux file systems and native OS tools;
2. Work with media files, including video formats, codecs, resolution, and frame rate (FPS);
3. Verify data integrity using checksum and verification tools;
4. Pack and unpack large data archives efficiently;
5. Automate data-related workflows using scripting languages;
6. Prepare, structure, and maintain datasets in structured formats;
7. Maintain cloud-based data storage and perform data migration;
8. Collaborate with Project, QA, and Technical teams to ensure smooth data operations;
9. Clearly and consistently document workflows, processes, and task updates.

Technical Skills:

1. Strong knowledge of Linux file systems and administration (Ubuntu/Debian, 2+ years);
2. Experience with Windows OS administration;
3. Proficiency in Python and Bash / Shell scripting;
4. Experience with archive management tools for large datasets;
5. Knowledge of checksum verification tools (md5sum, sha256sum);
6. Tools for checking video properties, codecs, and formats;
7. Solid knowledge of JSON and CSV formats;
8. Experience with cloud storage platforms: AWS S3, Google Cloud Storage, or Azure;

9. Familiarity with JIRA, Slack, Confluence, and Google Docs.

    

Nice to Have:

1. Experience with point clouds / 3D data;
2. Strong understanding of complex technical specifications;
3. Experience working with large-scale datasets;
4. English & Communication;
5. English level B2 (Upper-Intermediate) or higher;
6. Ability to read and understand technical documentation and project requirements;
7. Clear written communication in English (reports, updates, documentation);
8. Participation in English-language meetings when required. 

Data Science UA is a service company with deep expertise in AI and Data Science. Our story started in 2016 with the first Data Science UA Conference in Kyiv, and since then, we’ve built one of the largest AI communities in Europe.

About the role:
We are looking for a hands-on Sr. Machine Learning / Computer Vision Engineer with strong practical experience in designing, training, evaluating, and improving vision systems for real-world applications. The ideal candidate combines solid theoretical ML/CV fundamentals with an engineering mindset and is comfortable taking ownership of the full pipeline, from data preparation and experimentation to model optimization and deployment.

Responsibilities:
- Design, train, evaluate, and improve machine learning and computer vision models for real-world production use cases
- Build and maintain end-to-end ML pipelines, including data collection support, preprocessing, feature engineering, training, validation, and inference
- Develop solutions across both computer vision and machine learning tasks depending on business needs
- Perform error analysis, diagnose model weaknesses, and drive improvements in accuracy, robustness, and reliability
- Select and justify appropriate methods and model architectures based on dataset characteristics, product constraints, and deployment requirements
- Work with challenging real-world data, including noisy, limited, imbalanced, or weakly labeled datasets
- Collaborate with engineering and product teams to translate business problems into practical ML solutions
- Contribute to production-ready development with a focus on maintainability, reproducibility, and performance

Requirements:
- 3–5+ years of professional experience in Machine Learning / Computer Vision
- Strong senior-level practical expertise in computer vision, machine learning, and applied model development
- Hands-on experience with tasks such as object detection, image classification, anomaly detection, feature-based approaches, or similar
- Solid understanding of classical ML methods, including tree-based models, linear models, feature engineering, model selection, and evaluation
- Strong Python skills and practical experience with PyTorch, OpenCV, and common ML tooling
- Experience building full ML workflows including data preparation, augmentation, preprocessing, training, validation, testing, and deployment handoff
- Strong understanding of model evaluation, debugging, overfitting, generalization, optimization, and experiment-driven improvement
- Ability to write clean, modular, maintainable code and independently own technical solutions
- Strong analytical thinking, engineering maturity, and problem-solving skills

Nice to Have:
- Experience in adjacent ML domains such as time-series, audio, or NLP
- Experience with embedding-based methods, metric learning, retrieval systems, or memory-bank approaches
- Practical experience with model optimization techniques such as quantization, pruning, distillation, or related efficiency-focused approaches
- Experience working with real-world industrial datasets and ambiguous problem formulations
- Knowledge of software engineering best practices, reproducible experimentation, and pipeline design

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

Project

The project focuses on a deep refactoring and optimization of the reporting ecosystem combining Salesforce CRM and Tableau. The main goal is to redesign current data flows, replacing the bulky and slow architecture with a modular system of reusable components. You will work on a process redesign to ensure speed, data accuracy, and ease of future system maintenance.

Responsibilities

• Development and Redesign: designing and supporting complex interactive visualizations in Tableau Desktop with a focus on modularity.
• Architecture Optimization: transforming bulky data flows into a fast and stable reporting system.
• Integration and Setup: working with data streams from Salesforce CRM and ERP systems (SAP, Odoo, MS Business Central).
• Technical Optimization: performance tuning (Data Extracts, calculated fields, SQL query optimization).
• Business Collaboration: gathering requirements from stakeholders and translating them into clear technical specifications for visualization.
• Data Governance: ensuring data accuracy, integrity, and security (including Row-Level Security).

Requirements

• Must-have:
  • 1.5-2+ years of commercial experience with Tableau (Desktop, Server/Cloud) or other BI tools.
  • Strong SQL skills (writing complex queries, joins, CTEs).
  • Understanding of CRM and ERP system architecture (how data is stored and interconnected).
  • Intermediate+ English level (for technical communication and documentation).
• Nice-to-have:
  • Experience with Tableau and Salesforce integration (a significant plus).
  • Experience with Tableau Prep or other ETL tools (Alteryx, KNIME).
  • Tableau Desktop Specialist or Certified Data Analyst certification.
  • Experience with cloud data warehouses (Snowflake, BigQuery, AWS Redshift).

Conditions

• Collaboration Type: Part-time (Freelancer / Contract).
• Location: Remote.
• Schedule: Flexible (details to be discussed based on your availability).

Selection Process

1. Recruiter screening.
2. Technical interview with the Tech Lead.
3. Offer.

Position Overview

We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!

Key Responsibilities:

• Create statistical summaries to support hypothesis testing and data-driven decisions during EDA
• Implement data preparation and feature engineering pipelines for the models
• Plan and implement algorithms for predictive modeling.
• Provide continuous improvement of models in production
• Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/
• Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists.
• Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general.
• Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders.
• Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.

Required Skills and Qualifications:

• Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer.
• Proficient in building custom neural networks using PyTorch.
• Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling 
• Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax).
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus.
• Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures.
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries
• Solid understanding of statistics and data analysis.
• Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps.
• Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting.
• Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialization and deployment of models for real-time services.
• Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly.
• Proficiency in using Git for version control and collaboration.
• Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds.
• Certifications in deep learning are preferred.
• Excellent command of spoken and written English.
• Strong self-management, time management, and organizational skills.

• Ability to work under a structured management system while independently handling creative tasks.

   

What We Offer:

• Competitive remuneration package.
• Bonuses
• Professional mentorship and guidance from experienced team members.
• Opportunities for professional growth and continuous learning.
• A dynamic and collaborative work environment.
   

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

• Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
• Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
• Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
• Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.