Jobs Data Science

Department/Project Description

GlobalLogic takes an opportunity to partner with a leading global threat intelligence platform to design and deliver an enterprise-scale, Human-in-the-Loop (HITL) AI agent platform. The initiative centers on accelerating expert analyst decision-making by augmenting high-complexity threat intelligence workflows with cutting-edge generative and agentic AI systems.


Job Description

Essential qualifications

• MSc or PhD in NLP, information retrieval or machine learning with publications, or equivalent industry research experience.
• 5+ years of applied ML, with models in production use.
• Deep experience fine-tuning transformer encoders with PyTorch and Hugging Face.
• Multi-label and imbalanced classification, probability calibration and threshold optimization.
• Learning from user feedback: learning-to-rank, active learning, bandit/exploration methods or counterfactual evaluation.
• Rigorous experiment design and statistical analysis.

Desirable qualifications

• ModernBERT or other long-context encoder models.
• Multi-stage ranking or recommender systems.
• LLM post-training (SFT, LoRA, DPO), reward or judge models, and reranker or embedding fine-tuning.
• Vertex AI Training and Pipelines.
• Experience in security, threat intelligence or fraud.

Job Responsibilities

Key responsibilities

• Fine-tune, evaluate and calibrate ModernBERT for multi-label alert classification and high-recall shortlisting.
• Design the two-stage triage cascade: model thresholds, the hand-off to the LLM, and how each stage is measured.
• Convert analyst feedback into training data through label cleaning, active learning and defined retraining criteria.
• Correct for selection bias through exploration sampling of rejected alerts and counterfactual evaluation.
• Design the dynamic few-shot strategy:
  how decision points are represented
  how examples are selected
  how conflicting or stale human decisions are handled.
• Define the feedback and reward schema with the Lead Agent Engineer.
• Set offline and online evaluation, and review retrained models before production promotion.

We’re looking for a Senior Data Scientist who can take a data problem from an initial business question to a solution that works in production.

This role is not only about building models. We’re looking for someone who is comfortable exploring imperfect data, challenging assumptions, choosing the right approach for the problem, and working closely with engineers and product teams to turn experiments into reliable solutions.

What you’ll work on:

• Explore and analyze complex datasets to understand patterns, dependencies, and opportunities.
• Turn business and product questions into well-defined data science problems.
• Design, train, evaluate, and improve machine learning and statistical models.
• Work on the full ML lifecycle: data exploration, feature engineering, experimentation, validation, deployment, and monitoring.
• Decide when an ML model is actually needed — and when a simpler statistical or analytical approach will do the job better.
• Define meaningful metrics and design experiments to measure the impact of proposed solutions.
• Work with Data and ML Engineers to bring models into production and keep them reliable over time.
• Investigate model performance, data quality issues, drift, and unexpected production behavior.
• Present findings and recommendations in a way that is useful to both technical teams and business stakeholders.
• Help shape our data science practices through code reviews, technical discussions, and mentoring.

What we’re looking for:

• 5+ years of hands-on experience in Data Science or Machine Learning.
• Strong Python skills and practical experience with Pandas, NumPy, scikit-learn, or similar tools.
• Strong foundation in statistics, probability, and machine learning.
• Experience working with real-world datasets where the data is not always clean, complete, or perfectly structured.
• Confident SQL skills.
• Experience building ML solutions beyond notebooks and prototypes.
• Good understanding of model validation, experimentation, feature engineering, and performance evaluation.
• Experience with production ML workflows and familiarity with MLOps practices.
• Experience with AWS, GCP, or Azure.
• Ability to explain technical decisions, trade-offs, and results clearly.
• English — Upper-Intermediate or higher.

It would be a plus if you have:

• Hands-on experience with LLMs / Generative AI, NLP, recommendation systems, forecasting, or computer vision.
• Experience with PyTorch or TensorFlow.
• Experience with tools such as Spark, Databricks, Snowflake, MLflow, or Airflow.
• Experience designing A/B tests and working with product experimentation.
• Experience mentoring other Data Scientists or taking ownership of technical decisions.

Build the core data engineering capability that enables WPP Open applications, AI agents, analytics products, and business workflows to securely discover, access, combine, govern, and activate data across enterprise systems, client environments, media platforms, and third-party providers.

We are seeking four senior engineering specialists who will be responsible for implementation and delivery of key platform capabilities. While architecture leadership is provided by the platform architecture team, these hires are expected to bring deep expertise, contribute to solution design, challenge assumptions, and guide implementation decisions based on industry experience.

Requirements

Implement the capabilities required to acquire, standardize, harmonize, and operationalize external marketing, media, commerce, and third-party datasets at scale. 

• Strong experience with SQL, Python, and cloud-based platforms like AWS, GCP, or Azure.
• Solid understanding of data modelling, pipelines and orchestration tools (Airflow, dbt, or similar).
• Familiarity with modern data ecosystems — e.g. Spark, Databricks, Snowflake, BigQuery or Redshift.
• Experience working with CI/CD, version control and testing best practices.
• A proactive approach to solving problems and improving systems.
• Excellent communication skills — you can translate technical concepts into language anyone can understand.
• A passion for data and how it can drive better decisions in media, marketing and beyond.

Experience with technologies and platforms such as

• Adverity, Fivetran, Airbyte
• Google Ads, DV360, Campaign Manager 360, Search Ads 360
• Meta, TikTok, Amazon Advertising, LinkedIn, Pinterest, Trade Desk
• Marketing, advertising, commerce, audience, or measurement data ecosystems

Job responsibilities

• Building and maintaining external data integrations
• Implementing reusable ingestion frameworks
• Standardizing and harmonizing media and marketing datasets
• Integrating third-party and client-owned data sources
• Supporting real-time and batch data acquisition patterns
• Providing expert input into data acquisition and onboarding approaches

United Tech is a global IT product company shaping the future of real-time social connection.

With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking.

Our platforms enable connection at scale fast, interactive, and deeply engaging.

The market is projected to exceed $206B by 2030, and we are already leading the evolution.

Founded in Ukraine, scaling worldwide. Are you in?

About the role: This is a role for a leader who thrives in a fast-moving product environment, where challenges fuel growth and every decision shapes the future. With United Tech you will have the freedom to design, build, and re-engineer processes from the ground up, working side by side with a team that values initiative, knowledge sharing, and bold goals. Your ideas will directly influence revenue, and you will see the tangible results of your work reflected in key financial metrics. We move fast, we cut through bureaucracy, and we take on complex challenges that push both personal and professional boundaries, limited only by the scale of your ambitions

In this role, you will

• Build, scale, and develop the Data Science team, including hiring, mentoring, and performance evaluation
• Define and execute a Data Science strategy aligned with business priorities
• Oversee the full lifecycle of DS projects from problem formulation to deploying models into production
• Prioritize initiatives based on business impact (ROI, time-to-market)
• Collaborate closely with product managers, analysts, engineers, and C-level executives

It’s all about you

• Proven ability to implement best practices in Data Science: reproducibility, A/B testing, ML monitoring
• Strong track record in maintaining model quality (performance, drift, latency)
• Advanced Python skills (pandas, sklearn, numpy, xgboost; pytorch/tf is a plus)
• High-level SQL expertise (large datasets, query optimization)
  Hands-on experience with ML pipelines, orchestration (Airflow, Prefect), and monitoring (Evidently, MLflow, Prometheus)
• Experience with GCP
• Solid understanding of A/B testing, causal inference, and statistics
• Familiarity with architecture fundamentals (API, data pipelines, microservices — integration level)
• Cloud experience with AWS or Azure
• Knowledge of distributed computation tools (e.g., Spark, CloudRun)
• Proven track record with generative AI/NLP model deployment
• Experience in startups or high-growth companies
• Publications, conference speaking, achievements on Kaggle, or open-source contributions

Would be a plus

• Experience optimizing company processes through AI solutions
• Implementation of AI tools across departments (development, support, marketing, etc.)

What we offer

Care and support:

• 20 paid vacation days, 15 sick leave days, and 6 additional days off for family events
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Financial and legal support
• Maternity Recovery Support Allowance
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule
• Modern equipment or depreciation of your own tools

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
• AI is an integral part of our work culture. We invest in modern AI tools, equip our teams with the skills to use them effectively, and foster an environment where technology helps people achieve better results faster
   

Hiring process

• Intro call
• Technical Interview
• Interview with Hiring Manager
• Final Interview
• Reference check
• Offer

We are looking for a Middle AI/ML 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.

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.
• Practical experience with RAG architectures, vector databases, and retrieval strategies
• 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).

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Project Description:

Envana is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-
making to optimize large-scale renewable and traditional energy portfolios. We're delivering a key client MVP
in February 2027, and the project continues into 2028. Our stack: Ruby on Rails, Node.js/TypeScript and
Python services, PostgreSQL, Snowflake and AWS. We're looking for an autonomous data engineer to
strengthen our data foundation through good modeling, clean schemas, reliability and automation.

Responsibilities:

Work closely with product teams to help define and execute technical criteria
Architect and maintain robust data ingestion pipelines that feed both our application and analytics
Design well-modeled, layered tables with clean schemas that turn raw data into analytics-ready data
Help onboard client data from a variety of sources, such as Databricks via Delta Sharing, and integrate it
with our existing services and workflows
Make pipelines reliable and automated: data quality tests, monitoring, safe reprocessing and schema
change handling
Build a documented, well-tested data foundation that serves the app, analytics and future AI use cases

Mandatory Skills Description:

Mid-to-senior data engineer who has owned the design of production data pipelines end to end, working
as an autonomous IC
Designing and building production ingestion pipelines from APIs, files and shared-data sources, using a
workflow orchestrator (any tool, e.g. Airflow, Dagster or Step Functions)
Production experience with a cloud data warehouse (Snowflake preferred)
Strong SQL, plus production experience in Python (preferred) or Node.js/TypeScript
AWS or another enterprise cloud platform
AI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows
across a team and into the development lifecycle, including CI/CD
Strong English and communication skills

Nice-to-Have Skills Description:

dbt
Preparing data for AI/LLM use (e.g. semantic layers, metadata, retrieval-ready datasets)
Infrastructure as code (e.g. Terraform)
Exposure to energy, utilities or sustainability data

Languages:

English: B2 Upper Intermediate

We’re looking for a GCP data engineer with 4+ years of experience who can work independently across multiple client projects. Middle-level candidates are welcome, senior level is not required. The role involves working in US time zones.
 

Must-have skills

• Advanced BigQuery SQL, including scheduled queries, data transfers and incremental loads
• Python
• GCP services: Cloud Run, Cloud Scheduler, Cloud Functions, Secret Manager, IAM and Monitoring, managed across many projects at the same time
• REST APIs, webhooks and SFTP
• Git and Docker
• LLM APIs (OpenAI, DeepSeek, Perplexity) and prompt writing
   

Nice to have

• Terraform
• n8n
• Supabase and Postgres
• Clay
• Google Meridian
• Experience in lead scoring or marketing tech
• Experience optimizing GCP and LLM costs

Envana is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-
making to optimize large-scale renewable and traditional energy portfolios. We're delivering a key client MVP
in February 2027, and the project continues into 2028. Our stack: Ruby on Rails, Node.js/TypeScript and
Python services, PostgreSQL, Snowflake and AWS. We're looking for an autonomous data engineer to
strengthen our data foundation through good modeling, clean schemas, reliability and automation.

• Responsibilities:

  Work closely with product teams to help define and execute technical criteria
  Architect and maintain robust data ingestion pipelines that feed both our application and analytics
  Design well-modeled, layered tables with clean schemas that turn raw data into analytics-ready data
  Help onboard client data from a variety of sources, such as Databricks via Delta Sharing, and integrate it
  with our existing services and workflows
  Make pipelines reliable and automated: data quality tests, monitoring, safe reprocessing and schema
  change handling
  Build a documented, well-tested data foundation that serves the app, analytics and future AI use cases

• Mandatory Skills Description:

  Mid-to-senior data engineer who has owned the design of production data pipelines end to end, working
  as an autonomous IC
  Designing and building production ingestion pipelines from APIs, files and shared-data sources, using a
  workflow orchestrator (any tool, e.g. Airflow, Dagster or Step Functions)
  Production experience with a cloud data warehouse (Snowflake preferred)
  Strong SQL, plus production experience in Python (preferred) or Node.js/TypeScript
  AWS or another enterprise cloud platform
  AI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows
  across a team and into the development lifecycle, including CI/CD
  Strong English and communication skills

ZentixSoft is looking for a Senior Data Scientist! 🚀

Format: Full-Time Outstaffing, long-term engagement.

Location: Poland-based (Remote with readiness for occasional client meetings in Warsaw).
 

🧩 Responsibilities:

• End-to-End Ownership: Own modeling from problem definition to production deployment, analyzing multivariate time-dependent data for forecasting and classification.
• Feature Engineering: Build complex features around seasonality, lead-lag effects, weather impact, and regional supply chain dynamics.
• Model Benchmarking & Validation: Design and evaluate XGBoost, LightGBM, ARIMA, and deep learning sequence models using temporal cross-validation, uncertainty estimation, and explainability frameworks.
• Production Deployment: Productionize batch and API models on GCP alongside data engineers, implementing drift monitoring and retraining pipelines.
• Modern AI Integration: Prototype LLMs and AI agents where relevant for automated insights.
• Business Impact: Present quantitative findings, trade-offs, and metrics clearly to business stakeholders and non-technical decision-makers.
   

🎓 Our Perfect Match (Requirements):

• Commercial DS Experience: 5+ years in Data Science, applied ML, or quantitative analytics.
• Core ML & Data Stack: Advanced Python (Pandas, NumPy), ML frameworks (XGBoost / LightGBM / PyTorch / TensorFlow), and SQL.
• Cloud & Data Warehouse: Hands-on experience with Google Cloud Platform (GCP) and BigQuery is a MUST.
• Time-Series Expertise: Proven track record in time-series forecasting with concrete quality metrics (e.g., MAPE, RMSE, WAPE) in real-world environments.
• Location & Mobility: Candidate MUST be based in Poland and willing to visit Warsaw occasionally for client meetings.
• Communication: Fluency in English with the ability to explain complex quantitative models in business terms.
   

➕ Nice to Have:

• Experience with weather, geospatial, commodity, or supply-chain data.
• Bayesian methods, probabilistic forecasting, causal inference, or optimization.
• Production experience with LLMs or AI agents.
• GCP Data Scientist / ML Engineer certifications.
   

📍 Project Details:

⏳ Format: Full-Time, long-term outstaffing.

📍 Location: Remote in Poland (with occasional trips to Warsaw).

About the Client

The Client has been servicing technology solutions to the New York City real estate industry for over a quarter of a century.  As there is no widely accepted MLS in the Manhattan real estate industry, the Client’s application environment is the system that transmits up to the minute inventory from one firm to another.  This system has grown from 10 firms and 300 listings exchanged daily to close to 500 firms and approximately 10,000 listings exchanged daily in accordance with REBNY's RLS guidelines.

The Client supports a full service listings system application which is in use by approximately 300 firms.  Their products include but are not limited to the full service listing application supporting both the agent end user and data entry, a mobile listings application, a variety of listing feeds, off the shelf and customized VOW options, and marketing services which consist of custom brochures, an interface with the New York Times' Ad times 2000 and a proprietary advertising tool known as Premium Marketing Opportunity (PMO).  The Client has a long standing history of successful data conversions, integrations, and development of customized business solutions.

Project details

The project is the sophisticated Listing Management System web application that allows New-York real estate agents find the right properties available for sale and rent, generates various reports for the agents' clients.

Your Team

We've created the team of 30+ team-members in Ukrainie and not going to stop. Due to new business challenges, we are ready to hire 1 more team member.

For now, our friendly team consists of FullStack .Net developers, Front end developers, QAs, DBAs, Researchers, BA and Designer.

What's in it for you

• Interview process that respects people and their time
• Professional and open IT community
• Internal meet-ups and resources for knowledge sharing
• Time for recovery and relaxation
• Bright online and offline events
• Opportunity to become part of our internal volunteer community

Responsibilities

The right candidate will collaborate and report directly to customers' market analyst who is located in New York. 

His/ her daily routine will consist in identifying and entering the information about new real estate objects available in New York into the customer's software system. 

Training will be provided.

Skills

• Upper-intermediate (or higher) English to collaborate with US market analyst on the daily basis.
• High typing speed to enter information about new objects on New York real estate market into the customer's software (training will be provided).
• Technical background (experience working with Excel/data) or a technical education
• Analytical skills to be able to distinguish existing real estate objects against new one (training will be provided).
• Working hours should be close to New York working hours as possible. At least from 13-00 till 21-00 UA time. But ability to shift it even more to 22-00 and late will be a HUGE plus.
• Responsible attitude towards entering correct information into the customer's software.
• Desire to learn New York real estate domain.
• Knowledge or previous experience in real estate domain is not required but will be a HUGE plus.

We are looking for a Data Scientist to join our client — an international technology company in the AdTech industry, headquartered in New York with offices around the world. The company develops software for digital advertising analytics and verification: its platform evaluates the quality of every ad impression — preventing ad fraud, ensuring brand safety and suitability, and verifying viewability and geo-targeting. Its clients include some of the world's largest brands, such as Vodafone and Mondelez. The Data Scientist will take ownership of improving existing models, building statistically robust solutions, and translating business challenges into mathematical problems that are integrated into the platform.
 

Responsibilities:

• Enhance, fine-tune, and continuously improve existing modeling solutions, including customizing open-source libraries to meet project requirements;
• Perform exploratory data analysis and feature engineering to build statistically robust, interpretable models that reflect domain knowledge;
• Keep up with emerging methods and best practices in causal inference and experimental design;
• Translate complex business challenges into well-defined mathematical problems and communicate findings as clear insights and actionable recommendations to external stakeholders;
• Participate in code reviews and provide feedback on model architecture, system design, and technical implementation;
• Collaborate with product and engineering teams to integrate data science solutions into the company's platform.
   

Requirements:

• 5+ years of relevant industry experience with a BA or BSc in science or engineering, or 2+ years of professional experience with an MSc or PhD in a related field;
• Solid understanding of regression techniques, statistical hypothesis testing, and experimental design;
• Strong hands-on experience with the scientific Python ecosystem: NumPy, Pandas, Statsmodels, Matplotlib, and similar libraries;
• Strong communication skills and the ability to explain complex concepts clearly;
• A proactive, curious, and self-motivated approach with a genuine interest in continuous learning;
• Availability for occasional evening meetings (7–9 PM Kyiv time);
• Fluent English (C1).
   

Nice to have:

• Experience writing SQL queries for data extraction, transformation, and analysis;
• Practical knowledge of Bayesian methods and their application to predictive modeling;
• Experience with AWS;
• Hands-on experience with probabilistic programming frameworks such as STAN, PyMC, or NumPyro;
• Understanding of marketing analytics: campaign allocation, performance measurement, and marketing budget optimization.
   

What we offer:

• Paid vacation.
• Paid sick leave.
• Courses and learning opportunities.
• Flexible schedule and fully remote work from any location.
  
  Send your CV!

Dataforest are looking for a highly experienced Team Lead Data Science with a strong engineering and managerial background (10+ years in the domain). In this role, you will lead and scale our AI/Data Science practice, establish robust development processes, drive pre-sales and R&D activities, and effectively manage an engineering team of 8–10+ members.
 

 What you’ll do:

• Team Leadership & Management: Lead and grow the Data Science department (8–10+ people), perform 1-on-1s, technical assessments, and performance reviews.
• Architecture & Strategy: Define the AI/DS architecture and tech strategy, establish high-quality coding standards, and oversee code reviews.
• Business & Pre-sales: Collaborate closely with C-level executives (CEO/CTO) to shape development processes, lead pre-sale activities, and estimate complex AI projects for international clients.
• R&D & Solution Delivery: Drive complex AI projects from concept to production (High-Load systems, LLM/RAG solutions) and conduct R&D with cutting-edge technologies.
   

 You'll be a great fit if you have:

• 10+ years of total experience in Data Science, Machine Learning, Data Engineering, and Software Engineering.
• Management Experience: Proven track record of leading teams of 8+ engineers (Data Scientists, ML Engineers).
• AI & LLM Expertise: Deep practical knowledge of the modern AI stack: LLM, RAG, LangChain, LangGraph, and AI Agents.
• Core Tech Stack:
  • Mastery of Python, algorithms, and data structures.
  • Proven experience in building scalable ML/DS architectures and high-load production systems.
  • Solid understanding of MLOps, Docker, Kubernetes, and CI/CD pipelines.
• Business Analysis & Pre-sales: Demonstrated capability in project estimation, client communication, and translating complex business requirements into technical solutions.
• English: Upper-Intermediate (B2+) or higher for fluent communication with international clients.

We ensure your growth with:

• Great networking opportunities with international clients and challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary fixed in USD;

• Paid vacation and sick leave;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team-building activities and corporate events.

About RiskSeal

RiskSeal is a B2B startup serving fintech clients globally. Our API-first credit risk management platform enables digital banks and consumer lenders to simplify onboarding through data-driven insights.

We are growing rapidly and value collaboration with passionate, creative professionals. Join us to innovate, contribute your expertise, and grow alongside our team.

Headquarters: Dallas, Texas, USA

European Office: Warsaw, Poland

Learn more: https://riskseal.io/ 

Job Description

We are looking for a motivated Data Scientist to join our team in a fully remote role. The ideal candidate has experience in credit risk modelling, strong Python and SQL skills, as well as hands-on experience with scoring models. You will build and optimize advanced credit risk and anti-fraud models by leveraging machine learning, anomaly detection, and alternative data alongside traditional scoring. Working with client data, you will translate complex algorithmic outputs into clear, actionable insights for clients, partners, and internal teams.

What we're looking for:

• 2+ years of hands-on experience in credit risk and credit risk modelling (must-have)
• Solid knowledge of classical methods (logistic regression, decision trees, scorecards) and ML (boosting, random forests, neural networks)
• Strong Python and SQL skills
• Background in a bank, fintech, or data vendor environment
• Experience with PD modelling, scoring, and portfolio performance metrics
• Practical understanding of credit risk strategy and portfolio management, including approval strategies, credit limits, and cutoff optimization
• Comfortable working end-to-end: from raw data to a validated, production-ready output
• Able to present findings clearly to non-technical audiences, including clients and business partners
• Upper-Intermediate English level or higher.

What you'll be doing:

• Build, validate, and improve credit risk and scoring models
• Work with our clients’ data to generate insights and deliver analysis that helps them make better decisions
• Present findings and new ideas directly to clients and partners
• Think about new analytical products and data solutions that RiskSeal can offer
• Collaborate with business, product, and tech teams to turn data insights into real value

Nice to Have

• Experience working with alternative data sources.
• Knowledge of model governance and validation frameworks.
• Experience presenting analytical solutions directly to clients.
• Exposure to fintech products, digital lending, or embedded finance.

What We Offer

● A fully remote, full-time role in a growing product fintech company
● A fast-paced environment with minimal bureaucracy and quick decision-making
● The opportunity to work on credit risk models, scoring solutions, and real client data
● Direct collaboration with business, product, and tech teams
● The chance to contribute to analytical products that create real value for clients
● Competitive compensation and opportunities for professional growth

We are looking for a Senior AI/ML Engineer to design, develop, and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will take ownership of developing production-ready machine learning and LLM-based solutions, from understanding business needs and exploring data to designing technical approaches, implementing solutions, and integrating them into Foundry workflows. You will work closely with data engineers, business analysts, and domain experts, contribute to technical decisions, and help establish best practices for building scalable and reliable AI solutions.

Key Responsibilities:

• Design and develop AI/ML solutions for predictive analytics, classification, forecasting, automation, and AI-assisted workflows within Palantir Foundry, leveraging Python, Ontology objects, pipelines, and workflows.
• Design, implement, evaluate, and optimize LLM/NLP and RAG solutions using Palantir AIP, including prompt engineering, embeddings, retrieval strategies, vector search, and text processing.
• Own the end-to-end lifecycle of AI solutions, from experimentation and model development to deployment, monitoring, and continuous improvement.
• Collaborate with data engineers to understand data sources, ensure data quality, and design efficient and scalable data processing approaches.
• Integrate AI solutions into production workflows and optimize them for accuracy, reliability, latency, scalability, and cost-efficiency.
• Contribute to technical architecture and design decisions, including model, framework, and tool selection; proactively identify technical risks, improvement opportunities and proactively propose solutions.
• Work with business and domain stakeholders to translate business needs into practical, scalable, and production-ready AI solutions, clearly communicating technical decisions and model limitations.
• Identify technical risks, limitations, and opportunities for improvement and proactively propose solutions.

Requirements:

• 4+ years of experience in machine learning, AI engineering, applied data science, or related fields.
• Strong Python skills and hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Strong practical experience with LLMs, NLP, or GenAI applications, including prompt engineering, embeddings, text processing, summarization, or similar use cases.
• Solid hands-on experience designing and implementing RAG architectures, vector databases, and retrieval strategies.
• Strong understanding of the ML lifecycle, including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.
• Experience working with both structured and unstructured data, including tabular data, time series, text, and documents.
• Ability to independently analyze ambiguous problems, propose technical approaches, and drive solutions from concept to implementation.
• Strong communication skills, with the ability to explain AI concepts, technical decisions, and model 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)

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

About the Company

We are a European IT company with 200+ specialists delivering SaaS platforms, enterprise solutions, and cloud-native products for clients worldwide. We focus on building strong, long-term teams and supporting continuous professional growth.

About the Internship & Project

We are looking for a Trainee Data Scientist to join a project delivered for a UK-based marketing data platform. The client’s platform connects various marketing channels under one roof, helping businesses understand customer retention and acquisition through advanced Single Customer View dashboards and personalization tools. You will contribute to real client projects, focusing on Marketing Mix Modelling (MMM) and causal marketing measurement. We are looking for someone with strong statistical reasoning who is motivated to build real-world data science skills, work with e-commerce datasets, and grow into a specialized role.

Responsibilities

• Prepare, clean, and process real e-commerce and marketing datasets
• Build, validate, and diagnose Marketing Mix Models (MMM) using Python
• Analyze seasonality, promotions, and pricing, as well as model adstock/carryover and saturation
• Calculate incremental revenue and ROAS, build response curves, and develop budget optimization models
• Work closely with the Head of Data Analysis and CTO, actively questioning model outputs to ensure statistical accuracy
• Compare MMM results with experiments and other attribution methods, visualizing findings and eventually explaining technical results in simple client-facing language

Requirements

• Good foundation in Python for data analysis (pandas, NumPy, SciPy, scikit-learn)
• Solid knowledge of statistics and regression
• Understanding of model validation and the clear distinction between correlation and causation
• Up to 3 links to pet projects or an academic project demonstrating your best Data Science skills
• English level: Upper-Intermediate

Why This Internship is Exciting

• Great opportunity to enter a specialized and rapidly growing field of Marketing Mix Modelling (MMM)
• Work with real e-commerce datasets and influence real commercial decisions
• Receive strong mentorship from experienced professionals ready to teach you MMM, e-commerce marketing, and attribution
• Gain exposure to advanced tools like Bayesian MMM, PyMC, Google Meridian, and Meta Robyn
• A clear path from an internship to a Junior role, with the potential to become the company’s internal MMM expert and transition into client-facing responsibilities