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in Latvia

Hi, I’m Reinis – a results-driven Data Scientist and Head of Data & Analytics with over 8 years of experience driving data strategy, building AI systems, and leading high-impact data science teams. My work spans multiple industries, including fintech, e-commerce, and telecommunications. I specialize in delivering robust machine learning models, advanced analytics, and end-to-end data architecture - all tailored to your business goals. I’ve led data transformations at startups and enterprises, built AI-powered products from scratch, and even improved customer acquisition by 20% through intelligent targeting. Whether you need to: Design and deploy scalable ML pipelines, Build predictive models for customer LTV, churn, or credit scoring, Integrate data systems across AWS, Redshift, Kafka, and more, Lead and scale your data team for long-term success... …I’m here to help. Let’s bring data to the heart of your decision-making. Work History Highlights Head of Data and Analytics – GloPros (2022 – Present) Designed AI-powered user profiling & anonymization pipelines Delivered strategic consulting on AI integration and data infra Data Lead – Jeff-app.com (2023 – 2024) Managed a team of 7 delivering BI & ML solutions Built LTV prediction models and credit scoring systems Led data migration & recruitment for data talent Data Scientist – Jeff-app.com (2021 – 2023) Boosted lead conversion by 20% with ML targeting models Created lead quality predictive systems Freelancer – Upwork.com (2020 – 2021) Built custom DNNs and NLP solutions for diverse clients

I am a data and systems specialist with a strong focus on trading, real-time analytics, and blockchain-based infrastructure. My experience spans the full lifecycle of data-driven systems — from advanced forecasting models in the energy sector to the design and implementation of high-performance trading platforms in the cryptocurrency domain. I specialize in building and optimizing low-latency, data-intensive systems that operate under real-time constraints. This includes developing arbitrage and trading algorithms, designing scalable data pipelines, and working with distributed architectures using technologies such as Python, Go, Rust, Redis, MongoDB, and ClickHouse. I combine deep expertise in statistical analysis, machine learning, and quantitative modeling with strong engineering skills to deliver robust, production-grade solutions. My background includes leading forecasting systems for energy trading, where I applied machine learning and neural networks to predict solar and wind generation, as well as directing the development of high-performance trading infrastructure in highly competitive blockchain environments. This gives me a unique ability to bridge business objectives with technical execution in complex, data-driven domains. I position myself as a hands-on consultant who not only defines strategy but also deeply understands system architecture, performance bottlenecks, and execution mechanics. I focus on delivering measurable impact — improving decision-making, optimizing performance, and building systems that scale reliably in fast-moving markets.

I am a data scientist with an economist's view of the world. During the last two years, I have learned and applied R, SQL, Microsoft Excel and Power BI in academic and business environments. My professional experience includes summer internships in a global container shipping company, MSC, and the largest retail bank in the Baltic region, Swedbank, and a full-time senior economist position at the central bank of Latvia.