Data Scientist

Mexico

Job Description

Welo Data works with technology companies to provide datasets that are high-quality, ethically sourced, relevant, diverse, and scalable to supercharge their AI models. As a Welocalize brand, WeloData leverages over 25 years of experience in partnering with the world’s most innovative companies and brings together a curated global community of over 500,000 AI training and domain experts to offer services that span:

ANNOTATION & LABELLING: Transcription, summarization, image and video classification and labeling.

ENHANCING LLMs: Prompt engineering, SFT, RLHF, red teaming and adversarial model training, model output ranking.

DATA COLLECTION & GENERATION: From institutional languages to remote field audio collection.

RELEVANCE & INTENT: Culturally nuanced and aware, ranking, relevance, and evaluation to train models for search, ads, and LLM output.

Want to join our Welo Data team? We bring practical, applied AI expertise to projects. We have both strong academic experience and a deep working knowledge of state-of-the-art AI tools, frameworks, and best practices. Help us elevate our clients' Data at Welo Data.

Main Duties

Provide the necessary machine learning/data science expertise, and collaborate with data analysts and data engineers, so that the Analytics Solutions team can:

Deploy analytical approaches and tools to support business stakeholders with cutting edge business intelligence and data visualizations.

Leverage the organization’s data assets to develop, maintain, and support the implementation of predictive models that improve business performance in areas such as on-time delivery (OTD), quality performance, and other TBD items.

Maintain familiarity and stay up-to-date on state-of-the-art machine learning/data science approaches applicable to the role.

Engage directly with business stakeholders across the organization to cultivate a working knowledge and familiarity with the realities of the business, problems to be solved, and opportunities to add value through data; leverage this knowledge to help the team turn analytical models into practical, value-added solutions.

Collaborate with product & development teams when and as appropriate to facilitate the deployment of predictive models into business-facing work surfaces and systems.

Contribute expertise, problem-solving capability, thought leadership, and supplementary bandwidth to ongoing efforts of the Analytics Solutions team, including the maintenance and ongoing development of Data Warehouse, its connection to various other data systems & assets, and ensuring the responsiveness of our BI reporting systems to the evolving needs of the business.

Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning; discerning where simple analytics solutions (e.g. a quick visualization) are preferable to complex solutions (e.g. machine learning).

Become proficient in, and compliant with team requirements around the intake and documentation of various initiatives and progress within existing product management platforms (e.g., Jira).

Experience

Hands-on experience working with directly with stakeholders in a business environment to provide data analytics support, create & present data visualizations, and devise ways to leverage various complex sources of data to generate actionable business insight.·

Mastery of common data science tools such as Python or R (and related code libraries), and experience using them to design and build predictive models for use in real-life business applications leveraging proprietary business datasets, to achieve defined performance improvement objectives.·

Preferred: a track record of deploying such models to end users; training users on how to interpret the outputs of the models and applying them to their regular business processes; and modifying/improving models over time to adapt to changing business needs.

Education

Education: B.Sc. or MSc in Machine Learning, Data Science or similar discipline with robust statistical, data analysis, and machine learning competency (or equivalent experience).

ANNOTATION & LABELLING: Transcription, summarization, image and video classification and labeling.

ENHANCING LLMs: Prompt engineering, SFT, RLHF, red teaming and adversarial model training, model output ranking.

DATA COLLECTION & GENERATION: From institutional languages to remote field audio collection.

RELEVANCE & INTENT: Culturally nuanced and aware, ranking, relevance, and evaluation to train models for search, ads, and LLM output.

Please mention that you found this job on MoAIJobs, this helps us grow. Thank you!