GRADERA
Technology
DataScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist at GRADERA. Skills: Machine learning, Data analysis, Data engineering, Statistical modeling. Collect datasets. Clean datasets”
Industry & Context.
Root cause analysis; Troubleshooting; Data-driven decision making
What They're Looking For.
Must Have
Proficiency in Python, Proficiency in R, SQL skills, Experience with Databricks, Familiarity with Azure, Familiarity with AWS, Experience with data warehouses, Experience with big data platforms, Knowledge of MLOps tools, Experience with streaming data, Solid foundation in probability, Solid foundation in statistics, Solid foundation in linear algebra, Solid foundation in experimental design
Nice to Have
Experience with deep learning, Experience with NLP, Experience with computer vision, Experience with Bayesian methods, Familiarity with real-time pipelines, Familiarity with streaming data pipelines, Open-source contributions, Published research
What You'll Do.
Conduct exploratory analysis
Assess data completeness
Assess data consistency
Investigate data lineage
Document data lineage
Identify data anomalies
Resolve data anomalies
Identify data inconsistencies
Resolve data inconsistencies
Identify data integrity issues
Resolve data integrity issues
Apply statistical techniques
Build machine learning models
Deploy machine learning models
Develop data-driven recommendations
Write production-ready code
Build self-serve analytics tools
How You'll Work.
Team & Collaboration
Partnering with data engineering; Partnering with business teams; Collaboration with data engineers
Full Job Description
ABOUT GRADERA Gradera is an AI‑Native Services firm pioneering Software‑Orchestrated Services™—a new enterprise transformation model where software orchestrates human expertise, digital workers, and enterprise systems to deliver governed, scalable outcomes. We help enterprises move beyond fragmented AI pilots, disconnected automation, and labor‑led models by redesigning how work gets done across operations, product, engineering, customer experience, data, and core workflows. OVERVIEW We are seeking a highly analytical and curious Data Scientist to transform complex, real-world data into meaningful insights and scalable machine learning solutions. In this role, you will work across the full data lifecycle—partnering with data engineering and business teams to explore, clean, and understand diverse datasets, and translating those insights into models, experiments, and data-driven recommendations. You will play a critical role in bridging raw data and business impact, developing a deep understanding of how data is generated, structured, and used. This includes conducting rigorous exploratory analysis, assessing data quality and lineage, and building robust analytical datasets that power advanced modeling and reporting. This role offers the opportunity to work with large-scale data platforms, cloud infrastructure, and modern machine learning frameworks, while contributing to impactful decision-making through experimentation, analytics, and self-service data tools. Role & Responsibilities - Collect, clean, and analyze large structured and unstructured datasets from multiple internal and external sources - Conduct thorough exploratory data analysis (EDA) to understand data distributions, relationships, outliers, and missing value patterns - Profile and audit datasets to assess data quality, completeness, consistency, and fitness for modeling - Investigate and document data lineage — understanding where data originates, how it flows, and how it transforms across systems -
Applying for this Data Scientist role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Ashby
- Ashby is a fast modern ATS — most applications take under 3 minutes.
- The resume parser is strong; verify parsed experience dates and job titles.
- Custom screening questions are often scored algorithmically — answer completely.
- Location field affects geo-based screening; use your actual metro area.
ANONYMOUS · UNFILTERED
What do employees actually say about GRADERA?
Real rants from real employees. Read before you apply.