Senior Data Scientist – Time Series, Forecasting Models

Job not on LinkedIn

🕒 June 25

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Marathon Talent

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2023

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Marathon Talent is a recruiting and talent strategy firm that helps companies hire top bilingual professionals from Latin America quickly. They provide end-to-end recruitment, fractional people and talent strategy, market research and salary studies, and advisory/mentorship services—powered by a network of 10,000+ professionals and flexible pricing (success fee, flat fee, or monthly retainer). Marathon embeds with client teams to solve hiring, compensation, culture, and org design challenges for startups and growing companies, with a focus on building bilingual LATAM teams and improving growth through better talent foundations.

📋 Description

• Lead forecasting initiatives by designing and implementing advanced time series models to predict sales and behavioural trends for thousands of customers. • Develop scalable machine learning solutions that power real-time decision-making across risk management, fraud detection, and product personalization. • Collaborate cross-functionally with product managers, engineers, and business stakeholders to translate complex data challenges into actionable insights and measurable business outcomes. • Drive innovation in fintech applications by experimenting with cutting-edge approaches (e.g., deep learning architectures, probabilistic forecasting, and transformer-based models). • Ensure compliance and transparency in model development, aligning with industry regulations and ethical standards for financial data usage. • Shape the data science strategy by identifying opportunities where predictive modeling can unlock new value streams and competitive advantages.

🎯 Requirements

• You have at least 5 years of experience with machine and deep learning in a practical setting. • You have a good understanding of fintech products, and risk management to interpret business data effectively. • You have a strong foundation in probability, statistics, and econometrics. • You have strong expertise in time series forecasting methods based on statistical analysis (ARIMA, SARIMA, SARIMAX, VAR, exponential smoothing, or state-space models), on Machine & Deep Learning (Random Forest, XGBoost, RNNs, LSTMs, or Transformers), or on Bayesian theory (BSTS, Prophet, or ensemble forecasting), among others. • You have deep knowledge of machine learning techniques for sequential data (RNNs, LSTMs, GRUs, Transformers). • You have strong proficiency in ML/DL frameworks in Python (e.g. Tensorflow, PyTorch, Scikit-learn). • You are comfortable consuming data through APIs, SFTP, or straight-up CSVs. • You care about scalable machine and deep learning solutions governed by low time and space complexity algorithms and methods. • You have experience with explainable AI, specially in the context of Deep Learning Forecasting time series methods. • You have a data-oriented mindset: you care about getting to the bottom of how to make decisions based on data. • You have stakeholder management experience, keeping everyone up-to-date with key findings and explaining in a non-technical way results, methodologies and processes for data-driven decision making.