Overview Cotiviti is a leading solutions and analytics company that leverages financial datasets to deliver deep insight into the performance of retail system. These insights uncover new opportunities for retail organizations to collaborate to improve their financial performance and accuracy along with reducing inefficiencies. Cotiviti is seeking a hands‑on Data Scientist to build production‑ready machine learning solutions that power the next generation of Retail Technology. You’ll work with large on premise and cloud datasets, apply AI/ML to real-world identification and validation challenges, and collaborate directly with auditors and engineers to deliver high‑impact results. This role is perfect for an ambitious technologist who wants to ship real models—not conduct research—and make a direct impact in a fast‑moving environment. This role aligns with our Retail Recovery Audit solution. Cotiviti Retail. This role can be located within the US or Canada (Ontario area only) Responsibilities - Work with key stakeholders both within R&D and Operations, along with product management to assess the potential value and risks associated with business problems that have the potential to be solved using machine learning and AI techniques. - Develop an exploratory data analysis approach to verify the initial hypothesis associated with potential AI/ML use cases. - Document your approach, thinking and results in standard approaches to allow other data scientists to collaborate with you on this work. - Prepare your final trained model and develop a validation test set for QA. - Work with production operations to deploy your model into production and support them in monitoring model performance. - Participate in other data science teams collaborating with your peers to support their projects. - Participate in knowledge sharing sessions to bring new insights and technologies to the team. - Participate in design sessions to continuously develop and improve the Cotiviti machine learning platform. - Provide End to End value-based solutions, including data pipeline, model creation and application for end user consumption. - Complete all responsibilities as outlined in the annual performance review and/or goal setting. - Complete all special projects and other duties as assigned. - Must be able to perform duties with or without reasonable accommodation. This job description is intended to describe the general nature and level of work being performed and is not to be construed as an exhaustive list of responsibilities, duties and skills required. This job description does not constitute an employment agreement and is subject to change as the needs of Cotiviti and requirements of the job change. Qualifications - MS or PhD. Degree in relevant discipline (Math, Statistics, Computer Science, Engineering or Health Sciences) or commensurate professional work experience. - 4-7 years’ experience in advanced analytics. - 3+ years’ experience in working in Big Data environments. - Significant experience with SQL, ability to write SQL queries to efficiently extract data from relational databases. - Experience developing machine learning models in an exploratory data analytics environment and working with others to develop production ready versions of the models that are deployed within operational environments. - Experience in using machine learning tools to develop production strength models including, but not limited to, Python, TensorFlow, pandas, numpy, scikit-learn, spark, scala, hive, impala. - Applied Machine Learning: Application of a variety of machine learning techniques to increase identification of payment integrity issues for our clients, reduce the cost of auditing processes or increase the quality of care and outcomes. Must have implemented machine learning solutions within production environments at scale. - Big Data Analysis: Strong ability to manage and analyze data in a Big Data environment using a variety of scripts, potentially including but not limited to Scala/Spark and Python as well as Cloud based ML/AI capabilities. Mental Requirements: - Critical Thinking: Ability to think critically and evaluate information objectively, considering different perspectives and potential implications before drawing conclusions or making recommendations. - Attention to Detail: must have a keen eye for detail to ensure accuracy in data analysis, interpretation, and reporting. - Quantitative Aptitude: Strong numerical skills are essential for conducting quantitative analysis, working with statistical methods and models, and manipulating data using mathematical operations. - Data Interpretation: skilled in interpreting data visualizations, charts, graphs, and other forms of data presentation to extract meaningful insights and communicate findings effectively. - Communication Skills: Effective communication skills are crucial for conveying complex technical concepts and insights to non-technical stakeholders clearly and understandably through written reports, presentations, and verbal discussions. - Curiosity and Learning Agility: A strong desire to learn and explore new methodologies, techniques, and tools in the field of data analysis and insights generation is essential for staying current with industry trends and best practices. - Resilience: The ability to handle pressure, adapt to changing priorities, and overcome setbacks is important in a fast-paced and sometimes ambiguous analytical environment. - Ethical and Integrity: Upholding ethical standards and maintaining integrity in handling sensitive data and information is paramount for building trust and credibility in the insights provided Physical Requirements and Working Conditions: - Remaining in a stationary position, often standing or sitting for prolonged periods. - Repeating motions that may include the wrists, hands, and/or fingers. - Must be able to provide a dedicated, secure work area. - be able to provide high-speed internet access / connectivity and office setup and maintenance. - No adverse environmental conditions expected. Base compensation ranges from $110,000 to $140,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. For information about our benefits package, please refer to our Careers page. This role is based remotely and all interviews will be conducted virtually. Date of posting: 03/16/2026 Applications are assessed on a rolling basis. We anticipate that the application window will close on 06/15/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected. #LI-REMOTE #LI-RA1

Location: Warsaw, Poland (fully remote or office, your choice) Salary: PLN 105 to 170/hour B2B Contract: B2B What this company does This is a data and analytics services company, founded in 2008, working with over 75 large consumer goods brands across 30 countries. The work covers AI and machine learning, supply chain analytics, customer analytics, data platforms, and digital commerce. Clients are big, the engagements are complex, and the expectations are enterprise-grade. Why this role exists The company is building and delivering GenAI solutions for large clients in retail, CPG, and manufacturing. They need someone who can both lead the technical direction of those projects and stay hands-on throughout the full build. This is not a research role and it is not a management-only role. You will make architectural decisions and also write the code. What you will do - Lead the design and discovery phase for GenAI projects: translate business problems into concrete architectures covering model selection, RAG, agents, fine-tuning, and guardrails - Build complete GenAI solutions end to end, covering data ingestion, retrieval layers, orchestration (LangChain, LlamaIndex, LangGraph), API and backend - Design RAG pipelines using vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks - Own prompting strategies, model selection, and fine-tuning approaches including LoRA, QLoRA, and supervised fine-tuning - Implement safety and governance controls: input/output filters, PII handling, audit logs, human-in-the-loop mechanisms - Gather technical requirements directly from client stakeholders and produce reliable delivery estimates - Mentor other data scientists and engineers on GenAI patterns, code quality, and best practices - Track the GenAI landscape actively and run targeted proof-of-concepts on emerging approaches What the job actually looks like - You will work directly with international clients, often translating complex technical choices into language that non-technical stakeholders can act on - Engagements are with large enterprises in retail, CPG, and manufacturing. These clients have complex legacy environments, change management processes, and compliance requirements - You will be responsible for both the architecture decisions and the code quality on the same project, with other engineers looking to you for direction - The work involves production systems, not pilots. If something breaks in production for a major retail client, you are part of the response What this role requires - 6 or more years in Data Science or AI engineering with a track record of shipping production systems, not just prototypes - 4 or more years writing production-ready Python for AI and ML workloads: clean, maintainable, deployable code - 2 or more years of hands-on production experience with LLM-based systems, including RAG pipelines, agent frameworks, and evaluation - The ability to make architectural decisions under uncertainty and defend them clearly to both technical and non-technical audiences - Fluent English for direct client communication What this role does not include - Research-stage or experimental-only work. Everything here is built to run in production - A small-team environment. You will be working within a structured consulting organisation with its own processes, governance, and delivery standards - Founder-level autonomy. You will have significant technical ownership, but within client contracts and delivery commitments Compensation and working conditions - PLN 105 to 170 per hour on B2B contract depending on experience - Fully remote or office-based, your choice - Workation policy available for defined periods - Dedicated onboarding buddy from day one - Unlimited Udemy access and 110 or more training opportunities per year - Internal promotion pathways: 76% of promotions are internal

This is us At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development. This is the job Within the telecommunications domain, we are actively seeking a Senior Data Scientist to strengthen our team focused on building AI-driven solutions that enhance customer experience and operational efficiency. You will be working on advanced Generative AI use cases, including conversational AI (chatbots and voice bots), as well as internal AI tools that support business teams in their daily operations. The role involves designing and scaling solutions such as RAG-based systems and intelligent assistants, enabling both customer-facing and internal automation scenarios. This is the team In this role, you'll become a vital member of a diverse and international Data Science team within the IT organization. The team works closely with multiple business units (B2C, B2B, Finance, Technology), delivering data-driven solutions that go beyond proof of concept and are designed for production from the very beginning. You will collaborate with data engineers, product stakeholders, and non-technical partners, contributing to end-to-end AI solution development - from ideation and prototyping to deployment and scaling. This is you - Master’s degree in AI, Machine Learning, Data Science, or a related field - 3–6 years of experience as a Data Scientist (preferably at Senior level) - Strong expertise in AI/ML and practical experience delivering business-impacting solutions - Hands-on experience with Generative AI, especially LLMs - Experience with NLP use cases (e.g. chatbots, voice bots, text processing) - Solid programming skills in Python and experience working with APIs, SQL, and Git - Experience designing and implementing production-ready solutions - Ability to communicate complex technical concepts to non-technical stakeholders Nice-to-have skills: - Experience with telecom domain or customer-facing digital products - Knowledge of Agentic AI, RAG systems, vector databases, and chunking strategies - Familiarity with LLM frameworks such as LangChain, LlamaIndex, LangGraph, AutoGen, or similar - Experience with AWS and/or on-premise deployments - Knowledge of Docker, Airflow, CI/CD pipelines (e.g. GitHub Actions/Runners) - Experience with Google AI/NLP ecosystem This is your role - Design, develop, and scale AI/ML solutions with a strong focus on Generative AI - Build and optimize NLP-based systems, including chatbots and voice assistants - Develop and productionize RAG-based solutions and AI-powered internal tools - Collaborate with cross-functional teams to translate business needs into technical solutions - Deliver proof-of-concepts and evolve them into scalable, production-ready systems - Work closely with data engineers to ensure robust deployment and integration - Contribute to building a data-driven culture by demonstrating measurable business impact What awaits you at Avenga? At Avenga, everyone matters. We provide equal opportunities in recruitment, career development, and leadership, regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to fostering a work environment where our diverse community of employees, candidates, and business partners actively shapes our growth. By bringing together people from different backgrounds and experiences, we build a workplace where everyone feels free to be themselves while honoring the boundaries of others.

Data Scientist (ML) Location: Remote, but within the UK. Salary: £55,000 - £65,000  Please note: We are unable to sponsor international visas at this time. About Nexus Mods Established in 2001, Nexus Mods is the largest video game modding platform on the internet - a household name in the PC gaming ecosystem. - 71M+ registered members - 800K+ mods for 4,000+ games - 21B+ mod downloads We’re currently focused on product modernisation, driving growth and building infrastructure for the next 10 years of community-powered modding. Our Role We are looking for the first Data Scientist to join Nexus Mods. This is an opportunity to build the intelligence layer on top of our data platform, and to unlock the ML capability that's been waiting for the right person. We have invested in the foundations, and defined the ML roadmap, so you won’t be starting from scratch. Instead, you’ll step into a high leverage role where your work immediately powers discovery, personalisation, and a thriving community and ecosystem.  You’ll tackle a uniquely rich dataset (~900k mods, ~71m users) and turn it into structured, actionable intelligence that helps millions of users find what they love faster. From day one, your models will ship, your systems will scale, and your impact will be visible in real user growth.  Responsibilities:  Build the foundation (Mod Classification) - Own the end to end pipeline, powering classification at scale (~900K mods), from labelling data to production models.  - Turn raw data into structured, high-quality metadata that unlocks search, filtering, and personalisation.  - Continuously improve model performance and data quality.  Drive Discovery & Recommendations  - Build recommendation models and improve search relevance to help users find the right mods faster.  - Leverage behavioural signals and unique datasets (e.g.dependency graphs) to power smarter personalisation.  - Directly impact engagement by increasing downloads, retention, and overall activity.