Join Excelya, where Audacity, Care and Energy define who we are and how we work. We believe in creating ambitious solutions and fostering an inclusive environment where collaboration and individual growth go hand in hand.

This role offers an exciting opportunity to support a strategic productivity initiative within a leading pharmaceutical R&D environment. As a Data Manager – Efficiency Engine, you will contribute to improving operational efficiency, optimizing data workflows, and implementing automation solutions to accelerate project delivery within Research and Translational Medicine activities.

Key Responsabilities :

At Zyte, we're pioneering the next revolution in web data extraction, empowering businesses to focus on innovation. Companies often struggle with challenges like navigating dynamic web structures, countering anti-scraping measures, and ensuring data accuracy. We tackle these obstacles by providing best-in-class tools for seamless, reliable web data extraction. With over a decade of expertise, we've become the trusted solution for over 3,000 companies and a million developers, helping them achieve a competitive edge and drive sustainable growth.

We are a diverse and enthusiastic team of data nerds, tech aficionados, and hackers. At Zyte, you'll join an inclusive community where everyone belongs. We thrive on collaborating with our smart, passionate teammates and customers to solve complex problems in data science and engineering.

Join us and be part of the data revolution!

About the Job

Reverse engineering is at the heart of how Zyte stays ahead in the banning war. We've cracked some of the hardest antibots on the web — but the ground shifts weekly: antibots ship new sensor formats overnight, obfuscation schemes mutate, and new fingerprinting surfaces appear faster than any team could chase by hand.

At Zyte, we're pioneering the next revolution in web data extraction, empowering businesses to focus on innovation. Companies often struggle with challenges like navigating dynamic web structures, countering anti-scraping measures, and ensuring data accuracy. We tackle these obstacles by providing best-in-class tools for seamless, reliable web data extraction. With over a decade of expertise, we've become the trusted solution for over 3,000 companies and a million developers, helping them achieve a competitive edge and drive sustainable growth.

We are a diverse and enthusiastic team of data nerds, tech aficionados, and hackers. At Zyte, you'll join an inclusive community where everyone belongs. We thrive on collaborating with our smart, passionate teammates and customers to solve complex problems in data science and engineering.

Join us and be part of the data revolution!

About the Job

Reverse engineering is at the heart of how Zyte stays ahead in the banning war. We've cracked some of the hardest antibots on the web — but the ground shifts weekly: antibots ship new sensor formats overnight, obfuscation schemes mutate, and new fingerprinting surfaces appear faster than any team could chase by hand.

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Data Scientist to own the part that comes before the system exists: what question is actually being asked, which method answers it, whether the answer holds up, and how anyone would know.The role is fully remote across Latin America, aligned to your client's working day.

You will not be handed a specification. Azumo has shipped models into production since 2016, and the work here starts with a client who knows what bothers them and does not yet know what to measure. Turning that into a model, a baseline, and a number someone can act on is the job.

Where this role sits

Azumo's engineering organization is built around four lanes. The Data Engineer lane owns pipelines, storage, and the retrieval layer. The AI Engineer lane owns production behavior. The Software Engineer lane owns AI-augmented product delivery. This role is the Data Scientist lane, and it owns the question and the method.

One question places the boundary: when the output is wrong, whose problem is it? "The method was inappropriate, or the question was the wrong one" is yours. "The system did the wrong thing with an appropriate method" is the AI Engineer's.

Not quite your profile? Check our other openings:

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring a Data Engineer to own the layer everything else depends on: ingestion and transformation pipelines, storage and warehouse design, and the retrieval infrastructure that AI systems query. The role is fully remote across Latin America, aligned to your client's working day.

You will not be building pipelines that work until the schema changes. Azumo has shipped production data systems since 2016, and the work here is judged downstream: whether a model can be trained on what you deliver, whether a retrieval query returns the right passage, whether a number survives being questioned by the client.

Where this role sits

Azumo's engineering organization is built around four lanes. The Data Scientist lane owns the question and the method. The AI Engineer lane owns production behavior. The Software Engineer lane owns AI-augmented product delivery. This role is the Data Engineer lane, and it owns pipelines, storage, and the retrieval layer.

One question places the boundary: when the output is wrong, whose problem is it? "The data was missing, stale, or wrong by the time it arrived" is yours."The system did the wrong thing with data that was correct" is the AI Engineer's.

Not quite your profile? Check our other openings:

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for a Principal Data Analytics will play a critical role in developing advanced analytical and machine learning solutions that support strategic initiatives across Sales, Vendor Management, Cloud, eCommerce, Finance, and Supply Chain. This role combines hands-on modeling, deep analytical thinking, and strong business partnership.

Responsibilities

Role Summary

The Lead AI Architect & Delivery Manager will serve as the technical authority and engagement lead for the client's TPRM AI Assistant project, backfilling the departing AI Lead. This role is responsible for driving the technical strategy of the Snowflake-native RAG solution, orchestrating the offshore engineering team, interfacing directly with FCB leadership (ED&A, TPRO, InfoSec SMEs), and ensuring the solution meets its tight production launch milestone.

About the Role

We are looking for an experienced Data Capability Manager to lead the delivery of a modern data platform for a strategic enterprise client, as part of one of our early and high-priority data transformation initiatives. The project is building on an initial phase that established the target architecture, delivery approach, and proof of concept. The next phase is focused on turning that foundation into a scalable, production-ready data platform using Microsoft Azure, with Microsoft Fabric at its core. As Data Delivery Lead, you will take ownership of the data workstream from planning through delivery. You will lead the data engineering team, work closely with project and architecture leads, and ensure that the platform is delivered to a high technical and delivery standard. This role is ideal for someone who combines strong data engineering experience with the ability to lead technical delivery and work confidently with both technical and business stakeholders.

What You'll Do

● Lead the delivery of the data platform workstream, from planning throughproduction.

● Translate the existing architecture and roadmap into clear technical deliverables and priorities.

● Lead and support the team throughout the delivery.

● Design and oversee data ingestion, transformation, modelling, and data quality activities.

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Various market research firms, including Forrester and Gartner, have recognised our business value and leadership. We solve complex analytical problems at scale and have built a reputation for delivering valuable data-driven solutions across various industries, including Pharma and Life Sciences.

The ideal candidate will bring a blend of hands-on analytics expertise, stakeholder management, and team leadership experience, along with the ability to translate business challenges into scalable data solutions.

RESPONSIBILITIES:

Azumo builds and operates production AI systems for companies ranging from seed-stage startups to Meta. We are hiring an AI Engineer to own what those systems do once they are live: retrieval pipelines, tool-using agents, evaluation harnesses, and the guardrails that keep them dependable in front of real users. The role is fully remote across Latin America, aligned to your client's working day.

You will not be building demos. Azumo has shipped production AI since 2016, and the work here starts where the prototype ends, making a system reliable, measurable, and affordable enough to put in front of customers.

Where this role sits

Azumo's engineering organization is built around four lanes. The Data Engineer lane owns pipelines, storage, and the retrieval layer. The Data Scientist lane owns the question and the method. The Software Engineer lane owns AI-augmented product delivery. This role is the AI Engineer lane, and it owns production behavior.

One question places the boundary: when the output is wrong, whose problem is it? "The method was inappropriate" is a Data Scientist question. "The system did the wrong thing with an appropriate method" is yours.

Not quite your profile? Check our other openings: