Data Scientist at Ascella Technologies, Inc. jobs

Job Openings XTN-55CD773 | DATA SCIENTIST About the job XTN-55CD773 | DATA SCIENTIST Functional overview We are looking to hire a Data Scientist / Data Analyst for a leading homegrown Singapore company who specializes in providing world-class communication, entertainment and digital solutions. Duties and responsibilities Collection, analysis, visualisation of data and presentation of analytical results for regular and ad-hoc reporting purposes to meet multiple information and strategic requirements of the various stakeholders within the department. The successful candidate will engage in the following activities: Research, collect, analyse and report on key indicators, for both regular and ad-hoc reporting purposes. Use data to identify trends, spot anomalies and deepdive in complex data sets to identify their root causes. Work with various data sources and develop, modify and maintain reports, dashboards to meet specific needs of various departments. Ensure high level of quality/ accuracy/ standard of work and service throughout Use number-crunching and slide-maker skills to use and present data beyond just numbers. Hone storytelling skills through visualisation techniques by building dashboards/graphs and presenting insights to a non-technical audience. Minimum qualifications At least a bachelor degree in quantitative disciplines (e.g. Mathematics, Computer Science, Statistics, Economics, etc). 2-3+ years relevant experience in Data Scientist role. Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy. Advanced level of proficiency in MS Excel (Power Pivot, VBA, Power Query) and Power Point. Experience in creating dashboards using Tableau and other visualization tools. Ability to work autonomously and in a fast-paced environment. Good verbal and written communication skills along with high attention to detail Apply for Position Or refer someone Share Facebook Line LinkedIn X (Formerly Twitter) Whatsapp EmailMid Level

posted 2 months ago

Amazon

Data Scientist II, Amazon Fulfillment Technology (AFT) Science

Bellevue, United Statesfull time$136K–184K

posted 5 days ago

Micron Technology

Data Scientist

full timeMid Level

posted 3 months ago

Micron Technology

DATA SCIENTIST, SMAI

, , map[@type:Country name:SGfull timeMid Level

verified Jun 12, 2026posted 3 months ago

Senior Cloud Engineer (Azure) in Brussels, Bruxelles-Capitale

BE - Data Scientist

full timeMid Level

verified Jun 12, 2026posted 3 months ago

Cloudflare

Data Scientist

verified Jun 18, 2026posted 2 months ago

TotalEnergies

VIE – Data Scientist & Data Analyst (H/F) – Belgique

Startseite ... Jobs suchen Jobbeschreibung VIE – Data Scientist & Data Analyst (H/F) – Belgiquefull timeEntry Level

posted 25 days ago

Micron Technology

Data Scientist

full timeMid Level

posted 17 days ago

Bain & Company

Data Scientist

General Information Job Title Data Scientist Job ID 108666 Work Areas Analytics, Data & Research, Management Consulting, Product Management & Innovation, Technology & Engineering Employment Type Permanent Full-Time Location(s) Madrid, Warsaw Description & Requirements WHAT MAKES US A GREAT PLACE TO WORKWe are proud to be consistently recognized as one of the world’s best places to work. We are currently the top ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 overall spot a record seven times. Extraordinary teams are at the heart of our business strategy, but these don’t happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.WHO YOU’LL WORK WITHAbout Coro℠The Coro℠ business unit brings together Bain’s proprietary suite of software-as-a-service (SaaS) and data-as-a-service (DaaS) tools, including cloud-based software, online capability assessments, and advanced analytics, focused on enabling Commercial Excellence for B2B companies.You’ll work closely with data scientists, data engineers, and software engineers to develop sophisticated approaches to entity resolution at scale. Your focus will be on experimentation and model quality, while your engineering partners will help bring successful approaches into production.WHERE YOU’LL FIT WITHIN THE TEAMAs a Senior Applied Data Scientist, you’ll focus on one of the most challenging problems in large-scale data: determining when records from different sources refer to the same real-world business.You’ll develop and test machine learning, embedding, and large language model (LLM) approaches that improve how we match and resolve complex entity data. You’ll explore how far emerging foundation-model techniques can improve match quality while ensuring solutions remain practical, scalable, and cost-effective across hundreds of millions of entities.This is a highly applied role where you’ll have the opportunity to experiment with emerging AI techniques, measure their impact, and work with engineering teams to turn the strongest ideas into scalable solutions.WHAT YOU’LL DODevelop Smarter Entity MatchingBuild and evaluate machine learning, embedding, and LLM-based approaches for entity resolutionImprove how our systems handle complex and messy data, including name variations, aliases, domains, websites, firmographic attributes, multilingual records, and data hierarchiesDevelop scoring and ranking approaches that distinguish genuine matches from lookalikes, duplicates, and unrelated entitiesEvaluate AI and machine learning techniques while balancing accuracy, scalability, and costDesign solutions for large-scale use, identifying where sophisticated models add value and where more efficient approaches can achieve comparable resultsImprove Experimentation & Model QualityDevelop robust approaches to measuring match quality, including precision, recall, false positives, false negatives, confidence, coverage, and manual review requirementsHelp build trusted benchmark datasets to compare new approaches with existing matching methods before production rolloutExplore LLM-assisted review and validation both as a matching technique and as a benchmark for more scalable approachesTranslate ambiguous matching challenges into clear hypotheses, experiments, metrics, and recommendationsConduct detailed error analysis to understand model behavior and identify opportunities for improvementBring Successful Approaches to ProductionPartner closely with data and software engineers to turn promising prototypes into production-ready matching solutionsProvide clear model specifications, expected behaviors, evaluation results, edge cases, and rollout criteriaHelp determine the right matching techniques for different data tiers, confidence levels, and cost profilesMeasure impact, diagnose regressions, and recommend improvements to models and matching logicClearly communicate trade-offs across model quality, scale, cost, latency, explainability, and operational riskABOUT YOURequired Qualifications5–8 years of relevant professional experience in applied data science, machine learning, or a related fieldStrong applied machine learning expertise, including hands-on experience building and evaluating models using real-world dataExcellent Python and SQL skillsPractical experience with embeddings, semantic similarity, LLMs, or related AI techniquesHands-on experience training supervised and unsupervised models, including classification and NLP applicationsWorking knowledge of neural networks and transformer architecturesExperience with machine learning frameworks such as TensorFlow, PyTorch, or PyCaretExperience retraining taxonomy classifiers or maintaining classification models in productionStrong experimental judgment, including the ability to define baselines, evaluation metrics, test sets, and error analysesAbility to clearly explain model behavior, technical trade-offs, and edge cases to engineering and business stakeholdersPreferred QualificationsExperience with entity resolution, record linkage, deduplication, or similar matching problemsExperience with ranking, similarity scoring, retrieval, clustering, or candidate-generation techniquesExperience applying LLMs or embeddings to large-scale business problems where performance, scalability, and cost are important considerationsExposure to large-scale data platforms such as Spark, Snowflake, Databricks, or BigQueryFamiliarity with company, domain, website, firmographic, or other business-entity data Go back Apply Share this job: LinkedIn X Emailfull timeSenior

posted 13 days ago

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