Woodlawn, MD · On-site
... Phonetics Encoding, Address Standardization Solid Python, Regex, and SQL experience, Excellent ... Data Hygiene & Management: Clean, transform, and manage large-scale datasets from diverse, complex ...
Woodlawn, MD · On-site
... Phonetics Encoding, Address Standardization Solid Python, Regex, and SQL experience, Excellent ... Data Hygiene & Management: Clean, transform, and manage large-scale datasets from diverse, complex ...
Woodlawn, MD · On-site
... Phonetics Encoding, Address Standardization Solid Python, Regex, and SQL experience Excellent ... Data Hygiene & Management: Clean, transform, and manage large-scale datasets from diverse, complex ...
Woodlawn, MD · On-site
... Phonetics Encoding, Address Standardization Solid Python, Regex, and SQL experience Excellent ... Data Hygiene & Management: Clean, transform, and manage large-scale datasets from diverse, complex ...
Center Square, PA · On-site
$123K - $139K/yr
Contribute to the promotion of SKF's sensing and encoder solutions internally and externally ... Review the SKF Data Privacy Consent Statement. #J-18808-Ljbffr
Center Square, PA · On-site
$123K - $139K/yr
Contribute to the promotion of SKF's sensing and encoder solutions internally and externally ... Review the SKF Data Privacy Consent Statement. #J-18808-Ljbffr
PA · On-site
$123K - $139K/yr
Contribute to the promotion of SKF's sensing and encoder solutions internally and externally ... Review the SKF Data Privacy Consent Statement. #J-18808-Ljbffr
PA · On-site
$123K - $139K/yr
Contribute to the promotion of SKF's sensing and encoder solutions internally and externally ... Review the SKF Data Privacy Consent Statement. #J-18808-Ljbffr
Boston, MA · On-site
$160K - $180K/yr
More importantly, you will work with engineering to encode those abilities into software and train Newton to think like a data scientist. The data science team is small, so your work reaches ...
Boston, MA · On-site
$160K - $180K/yr
More importantly, you will work with engineering to encode those abilities into software and train Newton to think like a data scientist. The data science team is small, so your work reaches ...
Senior Research Data Scientist, Meridian AI Share Senior Research Data Scientist, Meridian AI ... By encoding human econometric reasoning into Large Language Model (LLM) driven workflows, you will ...
Senior Research Data Scientist, Meridian AI Share Senior Research Data Scientist, Meridian AI ... By encoding human econometric reasoning into Large Language Model (LLM) driven workflows, you will ...
Woodlawn, KY · On-site
Deep understanding of data matching strategies, including Blocking and Indexing, String Distance Metrics, and Phonetic Encoding. * Experience applying TD-IDF and Cosine Similarity for text ...
Woodlawn, KY · On-site
Deep understanding of data matching strategies, including Blocking and Indexing, String Distance Metrics, and Phonetic Encoding. * Experience applying TD-IDF and Cosine Similarity for text ...
Senior Research Data Scientist, Meridian AI Share Senior Research Data Scientist, Meridian AI ... By encoding human econometric reasoning into Large Language Model (LLM) driven workflows, you will ...
Senior Research Data Scientist, Meridian AI Share Senior Research Data Scientist, Meridian AI ... By encoding human econometric reasoning into Large Language Model (LLM) driven workflows, you will ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
Experience developing features from high‑cardinality categorical data using techniques such as aggregation, frequency encoding, target encoding, embeddings, graph features, or representation ...
... Encoding, Address Standardization \n \n * Solid Python, Regex, and SQL experience\n \n * Excellent ... Data Hygiene & Management: Clean, transform, and manage large\-scale datasets from diverse, complex ...
... Encoding, Address Standardization \n \n * Solid Python, Regex, and SQL experience\n \n * Excellent ... Data Hygiene & Management: Clean, transform, and manage large\-scale datasets from diverse, complex ...
East Syracuse, NY · On-site
$15 - $19.50/hr
High mechanical aptitude. * 1+ years of related work experience in high volume data entry / order taking / admin clerk / multiple and repetitive transaction encoding or info taking. * Background in a ...
East Syracuse, NY · On-site
$15 - $19.50/hr
High mechanical aptitude. * 1+ years of related work experience in high volume data entry / order taking / admin clerk / multiple and repetitive transaction encoding or info taking. * Background in a ...
Mclean, VA · On-site
BT-388 - Data Scientist Skill Level- Subject Matter Expert Location: McLean, VA (fully on-site, no ... Demonstrated academic or professional experience using encoder-decoder and generative language ...
Mclean, VA · On-site
BT-388 - Data Scientist Skill Level- Subject Matter Expert Location: McLean, VA (fully on-site, no ... Demonstrated academic or professional experience using encoder-decoder and generative language ...
Mclean, VA · On-site
BT-388- Data Scientist Skill Level- Subject Matter Expert Location: McLean, VA (fully on-site, no ... Demonstrated academic or professional experience using encoder-decoder and generative language ...
Mclean, VA · On-site
BT-388- Data Scientist Skill Level- Subject Matter Expert Location: McLean, VA (fully on-site, no ... Demonstrated academic or professional experience using encoder-decoder and generative language ...
A Data Encoder is responsible for inputting, updating, and maintaining accurate data in computer systems or databases. They ensure data integrity by verifying and correcting information as needed. The role often involves handling confidential records, organizing files, and generating reports. Strong attention to detail, typing skills, and familiarity with data management software are essential for this position.
A Data Encoder is primarily responsible for accurately inputting and updating information into digital databases or systems, often working with large volumes of data from paper or electronic sources. Typical daily tasks include reviewing documents for errors, verifying data for completeness and accuracy, and organizing files for easy retrieval. Data Encoders may also collaborate closely with other administrative staff or departments to ensure that records remain up-to-date and accessible. In some organizations, they also assist with basic data analysis or generate routine reports to support business operations.
To thrive as a Data Encoder, you need excellent attention to detail, fast and accurate typing skills, and a high school diploma or equivalent as a common minimum qualification. Familiarity with data entry software, spreadsheet applications like Microsoft Excel, and sometimes database management systems is typically required. Strong organization, time management, and the ability to work independently or as part of a team are valuable soft skills in this role. These skills are crucial for ensuring the accuracy, reliability, and efficiency of data processing tasks within various industries.
Cities with the most Data Encoder job openings:
The most popular types of Data Encoder jobs are:
States with the most job openings for Data Encoder jobs include:
For Data Encoder jobs, the most frequently searched job titles are:
Woodlawn, MD • On-site
Other
Posted 4 days ago
Position Title: Senior Data Scientist
Location: Maryland
Years of experience required: 18+ Years
**Selected candidate must be able to obtain and maintain a public trust clearance**
**Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week**
Key Required Skills:
Strong practical experience with Natural Language Processing (NLP), Text Processing, and Information Extraction concepts including Named Entity Recognition, Blocking and Indexing, String Distance Metrics, TF-IDF/Cosine Similarity, Phonetics Encoding, Address Standardization Solid Python, Regex, and SQL experience, Excellent Communication skills
Position Description:
Develop Analytics Solutions: Design, implement, and maintain advanced data processing and entity resolution pipelines using Python and SQL on enterprise data platforms.
Data Hygiene & Management: Clean, transform, and manage large-scale datasets from diverse, complex sources, ensuring absolute data integrity, reliability, and security.
Performance Optimization: Optimize complex SQL queries and database operations to ensure efficient data access, processing, and scalability.
Engineering Standards: Actively participate in code reviews, enforce version control, and uphold best practices for code quality, reproducibility, and data privacy.
End-to-End Delivery: Support data validation, testing, deployment, and post-implementation monitoring in a fast-paced environment.
Skills Requirements:
Foundation for Success (Basic Qualifications)
Bachelor's degree in Statistics, Applied Mathematics, Computer Science, or Information Science with experience in NLP, Text Processing, Information Extraction, Python, SQL, Regex and specialized libraries/frameworks.
Overall 10+ years' experience in IT industry
Factors To Help You Shine (Required Skills)
**Selected candidate must be able to obtain and maintain a public trust clearance**
**Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week**
**Master's and 10+ years of experience, Bachelor's and 12+ years of experience or 18+ years in lieu of a degree**
Strong practical experience with Natural Language Processing (NLP), Text Processing, and Information Extraction including:
Practical knowledge of Named Entity Recognition and Address Standardization to extract and clean unstructured text data.
Deep understanding of data matching strategies, including Blocking and Indexing, String Distance Metrics, and Phonetic Encoding.
Experience applying TD-IDF and Cosine Similarity for text comparisons and information retrieval.
Strong Python development skills for building analytics solutions and manipulating data.
Advanced SQL proficiency for complex data querying, optimization, and database operations.
Practical experience using Regex for advanced text processing, data cleansing, and pattern matching.
Familiarity with specialized libraries and frameworks including:
Linkage libraries such as Splink / FastLink, Dedupe, or recordlinkage
Core Python data science libraries, specifically spaCy for NLP tasks and Scikit-Learn for general machine learning and clustering
Familiarity with code reviews, version control, and maintaining data security and reproducibility standards.
Excellent communication skills.
How To Stand Out From The Crowd (Desired Skills)
Prior experience delivering IT or data initiatives within federal, state, or local government environments
Proven ability to operate independently, take ownership of data pipeline architectures, and drive projects from data discovery through to post-implementation.
Experience retrieving, migrating, and manipulating data from legacy and distributed systems, including PostgreSQL, DB2, Oracle, SQL Server, and Hadoop, as well as unstructured flat files.
Experience utilizing Jenkins to automate continuous integration, testing, and deployment (CI/CD) for data validation pipelines.
Experience with pipeline automation tools to schedule and monitor complex data cleansing jobs.
Strong ability to translate complex algorithmic decisions (such as probabilistic match thresholds) into clear business logic for executive leadership and non-technical stakeholders.
Excellent problem-solving skills and proven verbal/written communication skills when collaborating across cross-functional teams.
