Jobs Data Science

Evowill is looking for a Data Science Mentor to join our team. If you’re excited to share your knowledge with beginners in data science and machine learning, and enjoy teaching or want to try yourself in this role, we would be happy to collaborate!

You are:

• A Data Scientist/Data Analyst with 3–5+ years of experience in Data Science, Machine Learning, or Data Analytics;
• Patient, responsible, and well-organized;
• Interested in teaching and knowledge sharing;
• Curious and eager to learn, just as much as to teach;
• Proficient in writing clean, readable, and reproducible code;
• Passionate about helping others grow technically and intellectually;

• Comfortable working remotely with a flexible schedule (Ukrainian timezone).

   

We are:

• A Ukrainian-Colombian team;
• Working with Python, Data Science, and AI-related projects;
• Supported by experienced mentors who will help you onboard;

• Focused on growth, learning, and continuous improvement.

   

Technical skills:

• Strong proficiency in Python for data analysis;
• Hands-on experience with NumPy, Pandas, and Scikit-learn;
• Experience with both structured and unstructured data
• Solid understanding of machine learning concepts (classification, regression, clustering);
• Knowledge of statistics, basic and modern modeling techniques;
• Experience with Jupyter Notebooks or similar tools;
• Data handling skills: cleaning, preprocessing, and visualization (Matplotlib, Seaborn, or similar);
• Experience working with databases (SQL/NoSQL);
• Experience with XGBoost and Deep Learning models
• Experience with deep learning frameworks (TensorFlow, PyTorch, Keras);
• Familiarity with big data tools (e.g., Spark, BigQuery).
• Experience in NLP tasks such as topic modeling
• Understanding of embeddings, vector databases, and language models

• English — Upper-Intermediate or higher.

   

Nice to have:

• Experience with Git;
• Basic understanding of MLOps is a plus;
• Experience with cloud platforms (AWS, GCP, Azure);
• Experience deploying ML models;

We offer:

• Remote and flexible work;
• An international team (Ukraine + Colombia);
• Part-time opportunity;
• Professional growth;
• A supportive and collaborative environment.

Role overview

Partner with sales and delivery to win new data engagements. You'll translate vague client problems into credible, costed solution architectures, lead technical discovery, and present to stakeholders ranging from CTOs to procurement.

Responsibilities

• Lead technical discovery calls; turn business needs into reference architectures and high-level designs
• Build proposals, SoWs, and effort estimates jointly with delivery leads
• Run solution demos, POCs, and architecture walkthroughs for prospects
• Respond to RFPs/RFIs with clear technical narratives
• Stay current on the modern data stack and competitor offerings; advise sales on positioning and trade-offs

Required experience

• 5+ years in data engineering / data architecture, with at least 2 years in a client-facing or presale capacity
• Strong command of cloud data platforms across AWS, Azure, and GCP (at least two hands-on)
• Working knowledge of the major data warehouses and lakehouses: Snowflake, Databricks, BigQuery, Redshift
• Solid grasp of streaming (Kafka, Kinesis), orchestration (Airflow, dbt, Dagster, Prefect), and table formats (Delta, Iceberg)
• Comfortable estimating cost, effort, and risk across architectures you haven't personally built
• Excellent written and spoken English; able to lead a room of senior stakeholders

Nice to have

• Background in BI tooling (Power BI, Tableau, Superset)
• Experience with regulated industries (banking, insurance, healthcare)
• Certifications across two or more cloud/data vendors

We are looking for an experienced Senior Data Scientist to join our team and help unlock the full value of data across our platform, products, and business operations. In this role, you will apply advanced analytics, machine learning, and statistical modeling to generate actionable insights, improve decision-making, and drive innovation across the organization.

Responsibilities

• Analyze large, complex datasets to uncover trends, patterns, and insights that support strategic business and product decisions.
• Build predictive models to forecast business outcomes, improve operational efficiency, and support decision-making across multiple functions.
• Design and implement feature engineering techniques to improve machine learning model performance and accuracy.
• Partner with cross-functional teams including product, engineering, operations, and business stakeholders to identify opportunities and translate them into scalable data science solutions.
• Clean, preprocess, and structure data from multiple sources to ensure high-quality inputs for analysis and modeling.
• Develop, test, and deploy machine learning models for use cases such as classification, regression, clustering, recommendation systems, and forecasting.
• Evaluate and optimize model performance using appropriate statistical and machine learning metrics.
• Create dashboards, reports, and visualizations that clearly communicate findings and recommendations to technical and non-technical audiences.
• Automate recurring analysis, reporting, and model workflows to improve efficiency and consistency.
• Monitor production models and continuously improve performance, reliability, and business impact over time.
• Stay current with the latest advancements in data science, machine learning, and AI, and apply relevant innovations to PredictSpring’s platform and operations.

Requirements

• Excellent communication skills, including fluent verbal English, with the ability to explain complex concepts to non-technical stakeholders and collaborate effectively across teams.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Proven experience as a Data Scientist, with a strong background in machine learning, statistical analysis, and predictive modeling.
• Strong programming skills in Python preferred, or similar languages such as R, with hands-on experience using libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
• Expertise in building and deploying machine learning models for classification, regression, time-series forecasting, recommendation systems, and related applications.
• Strong experience with data wrangling, feature engineering, and working with structured and unstructured datasets.
• Proficiency in SQL for querying, transforming, and analyzing structured data.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud for model deployment and data workflows.
• Experience with data visualization tools such as Power BI, Tableau, or Python visualization libraries.
• Strong analytical thinking, problem-solving ability, and a passion for applying data science to real-world business challenges.

Preferred Qualifications

• Familiarity with big data and distributed processing tools such as Apache Spark, Hadoop, or Databricks.
• Experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch.
• Experience with natural language processing techniques such as text classification, sentiment analysis, or large language model applications.
• Strong foundation in statistical analysis, experimentation, and hypothesis testing.
• Experience collaborating with or supporting data engineering teams in building scalable data pipelines.
• Familiarity with version control tools such as Git.
• Strong business acumen and the ability to align technical solutions with business goals.
• Experience in retail, e-commerce, omni-channel commerce, or POS technology is a strong plus.

Why PredictSpring?

• Join a market-leading company shaping the future of omni-channel retail and modern POS.
• Work on high-impact challenges at the intersection of commerce, data, and customer experience.
• Collaborate with a talented global team in a flexible remote work environment.
• Enjoy opportunities for growth, learning, and professional development.
• Contribute to products used by some of the world’s most recognized retail and lifestyle brands.
• Be part of an innovative, collaborative, and data-driven culture focused on delivering measurable business value.

Senior Data Architect (Azure / Databricks)

We are looking for a Senior Data Architect who can design and implement robust and scalable data and analytics architectures on Microsoft Azure. You will work closely with customers and delivery teams, set technical direction, and take ownership of building modern data platforms based on Azure and Databricks.

This role includes daily hands-on work with data technologies and active participation in delivery projects.

What You Will Do

• Design and implement scalable data and analytics architectures on Microsoft Azure 
• Build and maintain data pipelines and data platform components 
• Define solutions for data ingestion, transformation, and storage 
• Translate business requirements into practical technical solutions 
• Collaborate with customers and delivery teams on architecture and implementation 
• Ensure solutions meet requirements for performance, reliability, and security 

Required Technical Skills

Data Architecture and Engineering

• Experience designing and implementing data and analytics architectures 
• Strong knowledge of SQL 
• Experience with ETL / ELT processes and data pipeline development 
• Experience with data modelling and data warehouse or lakehouse concepts 
• Experience integrating data from APIs, databases, and file-based sources 

Microsoft Azure

Hands-on experience with several of the following:

• Azure Data Factory 
• Azure Data Lake Storage (ADLS) 
• Azure Synapse Analytics or Microsoft Fabric 
• Azure SQL Database or SQL Server 
• Azure Databricks 

Programming and Tools

• SQL
• Python
• PySpark or Apache Spark 
• Experience building and maintaining production data pipelines 

Nice to Have

• Experience with Databricks 
• Experience with streaming or near real-time data processing 
• Understanding of data security and access control in Azure 
• Azure certifications related to data or architecture

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++

We are seeking an experienced Mid/Mid+ Data Scientist with expertise in Large Language Models (LLMs) such as GPT, Claude, and related technologies. The ideal candidate will have a strong background in natural language processing (NLP), machine learning, and deep learning models. They will play a critical role in developing and deploying cutting-edge LLM applications to drive innovation across our product lines.
 

Responsibilities:

• 5+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and solid software engineering fundamentals
• Proven experience building high-load, production-grade systems
• 2+ years of experience working with LLM and NLP-related tasks
• Hands-on experience with RAG pipelines and vector databases
• Strong understanding of modern deep learning architectures
• Experience with at least one deep learning framework (TensorFlow or PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Kubernetes
• Experience working with modern AI development tools (e.g., Claude Code, Cursor)
• Familiarity with Model Context Protocol (MCP)
• Experience with production LLM frameworks (e.g., vLLM)
• Experience training or fine-tuning LLMs
• Experience with cloud platforms (AWS, Google Cloud, Azure)
• Participation in Kaggle or similar competitions
• Ukrainian Native, English B2

Role Overview

We are a systematic prop trading firm operating at the intersection of CeFi and DeFi, with infrastructure deployed across 50+ exchanges and 20+ chains.
 

We are looking for a Senior Quantitative Researcher & Algorithmic Strategist to join the trading team. In this role, you will fully own the lifecycle of trading strategies — from research and backtesting to production deployment and optimisation.
 

This is a high-autonomy, high-impact position with direct collaboration with the founding team.
 

Key ResponsibilitiesStrategy Development

• Develop proprietary alpha signals or adapt existing strategies
• Design, backtest, and forward-test systematic trading strategies
• Conduct statistical validation (walk-forward, out-of-sample, regime analysis)
• Analyse capacity, decay, and correlation within the portfolio
• Prepare research documentation and performance reports
   

Engineering & Deployment

• Translate research into production-grade code (Python / C++ / Rust)
• Build algorithms for CEX market-making programs (Binance, OKX, Bybit)
• Improve order book logic (spread, inventory, execution efficiency)
• Integrate strategies into low-latency infrastructure
• Monitor live performance and conduct post-trade analysis
   

Market Microstructure & Execution

• Optimize fill rates, slippage, and latency
• Work with order book dynamics and execution logic
• Improve rebate capture and maker program performance
   

RequirementsHard Requirements (Must-have)

• Proven live trading track record (real P&L, not only backtests)
• Strong knowledge of crypto market microstructure
• Production-level coding in Python
• Working knowledge of C++ or Rust (preferred)
• Strong quantitative background (statistics, probability, time-series)
• Experience with exchange APIs (REST/WebSocket)
• Ability to own strategies end-to-end independently
   

Nice to Have

• Experience in prop trading / HFT / crypto quant firms
• Market-making algorithm experience
• Experience with CEX maker programs
• Familiarity with DEX / on-chain trading / MEV
• Experience in arbitrage strategies (CeFi–DeFi / cross-venue)
• Risk management systems (PnL limits, volatility sizing)
   

Academic Background

• Degree in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or similar
• Practical track record is prioritized over formal education
   

What We’re Looking For

• Strong ownership mindset over strategies and results
• Ability to explain and defend your edge
• Deep understanding of why strategies work (and fail)
• Attention to execution details (fees, latency, fills)
• Intellectual honesty and data-driven thinking
• Collaborative, non-ego-driven approach
   

Compensation

• Base Salary: Competitive (USD / stablecoin)
• Performance Bonus: P&L-based allocation (high-water mark model)
• Capital Allocation: Up to $100M+ per strategy (based on performance)
• Infrastructure: Full access to trading stack (50+ venues, low latency)
• Format: Remote-first, high autonomy
   

What We Offer

• Ready-to-use trading infrastructure (no need to build from scratch)
• Direct access to decision-makers
• Fast capital deployment
• Exposure to cutting-edge crypto markets (CEX + DEX)
• Collaborative research environment
• Flat team structure
   

Hiring Process

1. Call with Recruiter (30 min) — background and strategy discussion
2. Team interview (60 min) — strategy walkthrough
3. Final C-level Interview (30 min) 

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

Join PwC's Data & AI team and help design and deliver the AI and machine learning solutions that drive real business impact. We're growing quickly due to a strong pipeline of client work, and we're hiring across multiple seniority levels — from junior to senior Data Scientists.

Python is the core skill we expect. Depending on your strengths, you may focus on machine learning, statistical modelling, NLP, computer vision, or GenAI. Many roles also include "full-solver" flexibility — contributing where needed, including experimentation, prototyping, deploying models, or working end-to-end on AI use cases using modern platforms (including Microsoft technologies where relevant).

What You'll Do:

• Build AI That Solves Real Problems: Design, develop, train, and evaluate machine learning and statistical models across a wide range of business challenges.
• Turn Messy Data Into Insights: Explore, analyse, and visualize complex datasets to uncover patterns that matter. Perform feature engineering, data preprocessing, and selection to maximize model performance.
• Push the Boundaries With GenAI & NLP: Design and implement solutions leveraging Large Language Models, Retrieval-Augmented Generation (RAG), and NLP techniques.
• Experiment Rigorously, Deploy Confidently: Collaborate with data engineers and platform teams to move models from notebook to production, monitor performance over time, and support continuous retraining and improvement.
• Work Directly With Clients: Collaborate with clients across Western Europe and the USA to understand their business challenges, frame problems as data science opportunities, and communicate findings clearly. 
• Stay Ahead of the Curve: Keep up with the latest in AI/ML research, emerging techniques, and new tools. 

Who We're Looking For:

• Programming Skills (Key Requirement): Strong programming skills in Python (e.g. scikit-learn, TensorFlow, PyTorch, pandas, NumPy, Hugging Face, LangChain). The ability to write clean, maintainable, and reproducible code is essential.
• Machine Learning: Demonstrated hands-on experience building, training, and evaluating ML models. Strong understanding of supervised and unsupervised learning techniques, model selection, hyperparameter tuning, and cross-validation.
• Statistics & Mathematics: Understanding of core statistical concepts, probability, and linear algebra.
• NLP & GenAI (Highly Valued): Experience with natural language processing, text analytics, large language models, prompt engineering, RAG architectures, or other GenAI techniques.
• Computer Vision (Nice to Have): Experience with image processing, object detection, visual reasoning, or satellite imagery analysis is an advantage.
• Data Handling: Proficiency in SQL and experience with data wrangling, cleaning, and transformation.
• Cloud & MLOps (Nice to Have): Experience with cloud platforms (preferably Azure: Databricks, Azure ML, Synapse) or similar services on AWS/GCP is an advantage.
• Professional Background: At least 2–3 years of professional experience in data science, machine learning, applied research, or similar analytical roles.
• Language Skills: English at B2 level or higher.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

Overview
We are looking for a Machine Learning Engineer to design and implement intelligent systems that power personalized digital experiences across connected devices and mobile applications.

This is a hands-on role focused on applied machine learning and data engineering, ideal for someone who thrives at the intersection of ML models, data pipelines, and product integration. You will collaborate closely with backend engineers, data scientists, and product managers to bring ML-driven features into production and continuously optimize them based on real-world usage.

Responsibilities:

• Design, train, and deploy machine learning models for use cases such as personalization, recommendations, and visual analysis;
• Build and maintain scalable, production-grade data pipelines (batch and real-time);
• Collaborate with product and engineering teams to translate product ideas into ML-powered features;
• Implement model observability, monitoring, and retraining workflows;
• Optimize inference performance and model serving in resource-constrained environments (e.g., edge or mobile);
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;
• Work with backend teams to expose model outputs via APIs and integrate them into customer-facing experiences;
• Stay up to date with recent ML/AI advancements and evaluate promising methods for future implementation.

Requirements:

• 3+ years of experience in applied machine learning or data science;
• Strong knowledge of:
  • Supervised learning, recommendation systems, or computer vision;
  • Python and ML libraries such as TensorFlow, PyTorch, scikit-learn;
  • Building, deploying, and maintaining ML models in production.
• Familiarity with:
  • MLOps tools (e.g., MLflow, TFX, Airflow, Vertex AI);
  • Data pipelines and messaging systems (e.g., Kafka, BigQuery, dbt);
  • Model serving frameworks (e.g., FastAPI, TensorFlow Serving, TorchServe, ONNX);
• Comfortable collaborating with product, engineering, and analytics teams;
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Bonus: Experience with edge AI, mobile ML, or video/image processing pipelines.

About the role

We are looking for a Senior Data Scientist to lead the evolution of machine learning systems within a high-scale AdTech ecosystem.

This is not a “campaign optimization” role. You will work on the core decision-making systems (DSP level) — where pricing, bidding, pacing, and experimentation interact in real time across billions of events per day.

You will be shaping the “brain” of the platform: a set of interconnected systems where small improvements can have a large business impact.

What you’ll work on

• Pricing & Budget Scalability
  Scale budgets while maintaining performance and controlling overspend
• User Selection Optimization
  Improve CVR through smarter targeting and traffic selection
• Exploration Efficiency
  Reduce wasted spend while preserving learning
• Incrementality Measurement
  Measure true lift vs attributed performance
• Fraud Detection & Filtering
  Improve traffic quality and filtering strategies

What we expect from you

System-level thinking

• Ability to reason about interacting systems, not isolated models
• Understanding of:
  • auction dynamics
  • bidding vs pacing trade-offs
  • feedback loops between models
• Seeing problems beyond segmentation or heuristics

Strong experimentation mindset

• Designing experiments, not just running A/B tests
• Experience with:
  • metric design (proxy vs north star)
  • online vs offline evaluation gaps
  • interference and auction effects
• Ability to translate system changes into measurable impact

Ownership & impact

• Proven track record of driving business impact, not only building models
• Ability to explain:
  • expected vs actual impact
  • why results differ
• Performance accountability mindset

AdTech domain understanding

• Solid understanding of:
  • targeting vs bidding vs supply dynamics
• Experience working close to DSP / auctions/pricing systems

Collaboration maturity

• Ability to work across DS, MLE, and Product
• Understanding trade-offs and constraints
• Experience making decisions in ambiguous environments

Core responsibilities

• Turn ambiguous problems into testable hypotheses
• Design and run offline analysis + online experiments
• Use intermediate metrics to understand system behavior
• Build prototypes and iterate quickly
• Identify where system-level improvements are required
• Collaborate across teams to drive end-to-end impact

Requirements

• 5+ years in Data Science / Machine Learning
• Strong experience in high-frequency systems (AdTech / FinTech / similar)
• Python & SQL proficiency
• Experience with big data tools (Spark, Snowflake, etc.)
• Strong ML background (TensorFlow, PyTorch, or similar)
• Solid foundation in:
  • probability
  • statistics (frequentist / Bayesian)
  • causal inference
• Master’s or PhD in a quantitative field

Nice to have

• Experience with DSP / auctions / pricing systems
• Experience with large-scale experimentation

We are looking for a Computer Vision Engineer with a solid foundation in classical computer vision and hands-on experience implementing low-level CV algorithms. The ideal candidate will have exposure to SLAM, Visual-Inertial Odometry (VIO), and sensor fusion, with responsibilities adjusted according to experience level.

Responsibilities: 

• Implement and optimize low-level computer vision algorithms under guidance
• Contribute to modules related to feature extraction, tracking, matching, and geometric processing
• Assist in the integration and testing of SLAM/VIO components
• Perform experiments, analyze results, and help prepare reports
• Work closely with senior engineers to explore and apply recent CV research.

Required Qualifications:

• 1+ years of hands-on experience with classical computer vision
• Basic understanding of geometric computer vision principles
• Experience implementing low-level CV algorithms (e.g., filtering, feature detection, camera models)
• Familiarity with SLAM or VIO concepts
• Working knowledge of C++ and Linux
• Ability to learn quickly and navigate recent CV researc
• Degree or ongoing studies in a STEM field.

Nice to Have:

• Experience with Python
• Knowledge of neural networks and CV libraries/frameworks (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion techniques
• Familiarity with embedded or real-time systems

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.
   

About The Role

As a Senior/Lead Software Engineer in our Machine Learning department, you will take ownership of high-impact initiatives that drive product quality, monetization, and user experience. You’ll apply your expertise in Python, data analysis, and modern AI tools to build, deploy, and optimize ML solutions end-to-end. This is a hands-on technical role that blends data science and engineering to deliver measurable business outcomes. You’ll collaborate closely with cross-functional stakeholders and contribute to evolving areas such as LLMs, Generative AI, and ML infrastructure. The role offers exposure to complex data challenges and the opportunity to shape Pearl’s AI-driven capabilities.

What You’ll Do

• Build, train, and deploy ML models that improve product performance and monetization.
• Collaborate with data, product, and engineering teams across multiple internal initiatives.
• Design and implement data pipelines for extraction, transformation, and analysis.
• Apply statistical and machine learning techniques to real-world business problems.
• Work on projects involving LLMs and Generative AI technologies.
• Analyze large datasets to identify trends, insights, and optimization opportunities.
• Integrate ML models into production systems and monitor their performance.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders.
• Experiment with emerging AI tools and methodologies to enhance existing workflows.
• Ensure data quality, reliability, and scalability in all deliverables.

What We’re Looking For

• 3+ years of hands-on experience in ML Engineering or Data Science.
• 5-6+ years total experience in software or data engineering.
• Strong programming skills in Python.
• Proficiency in SQL for data querying and analysis.
• Solid understanding of data processing, analysis, and visualization.
• Experience with LLMs / Generative AI tools (e.g., OpenAI, Copilot, Cursor).
• Ability to build and deploy ML models end-to-end.
• Strong analytical and problem-solving mindset.
• Experience with .NET for integration work
• Upper-intermediate English proficiency (B2 or higher).
• Familiarity with Databricks or similar data platforms (nice-to-have).
• Exposure to AWS or other cloud-based ML environments (nice-to-have).

Why Join Us?

• High-Impact Data — Work with vast datasets generated by over a million daily visits, uncovering valuable insights.
• Collaborative Analytics Team — Join a team of 30+ skilled analysts who actively share knowledge and support each other.
• Cutting-Edge Tools & Techniques — Get hands-on experience with ML, Bayesian methods, and LLMs to solve real business challenges.
• Data-Driven Culture — Thrive in an environment where data informs every decision and drives continuous improvement.

Requirements: 
Address data is a central component of many processes within Westnetz. It is required for numerous applications, such as the installation of electricity meters, the connection of gas pipes, the billing of services or the deployment of technicians in the field.
Different types of address data are required depending on the use case. As part of a centrally managed expansion project, the address data system to be used by Westnetz for all central IT systems in future is to be fundamentally expanded. The main objective is to expand the address data repository with an additional address data pool in order to supply the required address data to the consuming systems.
In addition, enhancements will be implemented to make the system more user-friendly.

As part of the expansion of an address data master, the following services are to be provided:
- Performing the matching of various address data pools (geodata and attribute data) by developing a matching algorithm with adjustable thresholds
- Carrying out test management: creating test cases, executing the test cases, documenting the test results
- Documenting the interface tests
- Carrying out address data analyses and processing on Azure in SQL, Python and Spark to determine the quality of the address data

Profile:
- A degree in Computer Science, Business Informatics, Industrial Engineering or a related field
- Professional experience as a Data Scientist or in a similar role
- In-depth knowledge of Python, SQL and Spark
- Analytical thinking, structured approach to work