Data Scientist

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Applaudo

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2013

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Applaudo is a nearshore software development company that helps businesses accelerate their digital transformation. With over a decade of experience, Applaudo partners with some of the world’s most admired brands to streamline IT solutions, optimize delivery costs, and modernize their digital infrastructure. The company offers a range of services including innovation and experience design, development and maintenance, quality assurance, cloud solutions, artificial intelligence, and cybersecurity. Applaudo is known for its expertise in data solutions and app modernization, and has a strong presence in industries like sports, media and entertainment, retail, consumer packaged goods, and financial services. Headquartered in Austin, TX with offices in San Salvador, Applaudo blends top-tier software development talent with cutting-edge technology to drive business growth for its clients.

📋 Description

• Build and evaluate ML approaches for company/entity matching • Develop embedding and LLM-based matching approaches • Develop scoring and ranking methodologies to identify true matches and distinguish them from duplicates, lookalikes, and unrelated entities • Work with messy data, including names, aliases, domains, websites, firmographic attributes, multilingual records, and data hierarchies • Define benchmark datasets, metrics, baselines, and error-analysis processes • Design and execute experiments to validate hypotheses • Compare LLM-assisted approaches against lower-cost alternatives • Analyze model behavior, edge cases, and trade-offs • Consider inference economics and scalability from the beginning • Communicate experimental findings and recommendations to engineering and business stakeholders • Independently establish experimental pipelines and research approaches • Clearly document both successful and unsuccessful experiments

🎯 Requirements

• 5+ years of professional Data Science / Machine Learning experience • Strong applied Machine Learning fundamentals • Excellent Python and SQL skills • Hands-on experience with embeddings and semantic similarity • Practical experience applying LLMs to real-world problems • Experience with supervised and unsupervised learning • Strong experience with classification and NLP • Working knowledge of neural networks and transformer architectures • Hands-on experience with TensorFlow, PyTorch, PyCaret, or equivalent ML frameworks • Experience retraining or maintaining classification models in production • Strong experimental design and model evaluation skills • Experience defining baselines, metrics, test sets, and error-analysis processes • Ability to evaluate model quality and demonstrate measurable improvements • Strong understanding of scalability and ML inference costs • Strong English communication skills • Nice-to-have: entity resolution, record linkage, or deduplication experience • Nice-to-have: ranking and similarity scoring • Nice-to-have: retrieval, clustering, or candidate-generation techniques • Nice-to-have: LLM/embedding solutions designed for cost and scale constraints • Nice-to-have: Spark, Snowflake, Databricks, or BigQuery • Nice-to-have: experience with company, domain, website, or firmographic data • Nice-to-have: experience working with multilingual datasets • Strong analytical and experimental mindset • Intellectual honesty and willingness to communicate negative results • Strong autonomy and self-direction • Excellent written and verbal communication • Ability to defend technical recommendations with stakeholders • Strong problem-solving skills • Comfort working with ambiguity and large-scale datasets • Ability to balance model quality, cost, and scalability

🏖️ Benefits

• Remote work option