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We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.

Responsibilities

As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:

Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of Pecans Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

As part of our Automation team, you will play a key role in building and evolving a robust automation infrastructure that supports complex, scalable products.

You will help shape automation architecture, tooling, and best practices, work closely with R&D teams in an Agile environment, and directly influence the quality, reliability, and scalability of our platform.

This role combines hands-on automation development with system-level thinking.

In this role you will:
Design, develop, and maintain automation frameworks and test infrastructure
Write and maintain high-quality automated tests (API, integration, and UI)
Educate and collaborate with R&D teams on testing strategies, quality practices, and automation approaches
Shape automation architecture, design patterns, and development paradigms
Work closely with R&D teams daily in an Agile environment
Contribute to scalability, reliability, and quality improvements across the platform
Take ownership of automation solutions, from concept to production usage

As a Senior Backend Engineer, you'll be a key technical contributor to our team, working on distributed systems and helping shape our architecture.

You'll be joining a collaborative global team working on a strategic solution that's approaching its first major delivery. But this is just the beginning-new features and versions will continue to evolve, and your contributions will shape the product's future.

If you're passionate about complex distributed systems, end-to-end ownership, and making real product impact - this role is for you.



In this role you will:
Ownership mindset - You take responsibility for your work from conception to production
Collaborate globally - Work with a distributed team where clear communication and independence are essential.
Fast learner - You adapt quickly to new technologies and aren't afraid to dive into unfamiliar territory
Hands-on approach - You're comfortable rolling up your sleeves and getting into the code

were looking for skilled professionals to help shape our data platform and drive the next generation of trading technology.

In this role you will:
Design, implement, and maintain scalable data pipelines using Python and orchestration tools like Apache Airflow.

Take a leading role in evaluating and selecting foundational components of our data stack (e.g., Databricks vs. Snowflake).

Architect and optimize data workflows across AWS and on-premise environments.

Work with modern file formats (Iceberg, Parquet, ORC) and understand their trade-offs for performance, cost, and scalability.

Collaborate with analysts, engineers, and stakeholders to provide accessible and reliable datasets.

Help assess and implement frameworks such as DBT for data transformation and modeling.

Develop best practices and internal standards for data engineering, monitoring, and testing.

Contribute to the long-term vision and roadmap of Fin-on-exs data infrastructure.

We are looking for a Senior DevOps Manager to lead our global DevOps initiatives across hybrid environments (AWS and On-Prem). This is a highly technical leadership role focused on building a developer-first platform.

You will bridge infrastructure and R&D by designing scalable Kubernetes-based environments, building custom internal logic, automating complex workflows, and owning the traffic and API layer.

The ideal candidate is a hands-on technical leader with deep Kubernetes expertise, experience with ArgoCD, Helm, and Kong, and a strong software engineering mindset.

In this role you will:
Architect, build, and maintain scalable production environments across AWS and On-Prem using Kubernetes
Own and optimize the Kong API Gateway, including custom plugin development and traffic routing
Standardize application packaging using Helm and manage declarative deployments with ArgoCD
Build custom internal tools and logic using Python and Lua
Design, implement, and maintain fully automated CI/CD pipelines using GitLab CI
Work closely with R&D teams to identify pain points and automate manual processes
Implement Security as Code across CI/CD pipelines and gateway layers
Ensure infrastructure complies with privacy, security, and data protection standards
Manage, mentor, and grow a global team of remote DevOps engineers
Define technical roadmaps aligned with infrastructure scaling and R&D velocity