Website:
gradera.ai
Job details:
Company Description
Gradera is transforming the technology services industry with its innovative Software-Orchestrated Services™ (SoS™) model, designed to govern and optimize how work flows across humans, digital workers, and systems. By uniting advisory, platforms, and solutions into an orchestrated system of intelligence, Gradera enables organizations to achieve measurable and governed outcomes at scale. Rooted in continuous learning and adaptive intelligence, this approach drives sustained innovation while amplifying human expertise. Founded by the leadership that shaped PK Global, Gradera is setting a new standard for enterprise modernization and evolution through cutting-edge frameworks like Neural IQ™, NexusFlow™, PhiSphere™, and Value360™. Our goal is to help enterprises become self-improving, adaptive, and future-ready systems.
🔍 Role & Responsibilities
- Collect, clean, and analyze large structured and unstructured datasets from internal and external sources
- Perform exploratory data analysis (EDA) to understand distributions, relationships, outliers, and missing values
- Profile and audit datasets to ensure data quality, consistency, and completeness
- Analyze and document data lineage, transformations, and dependencies
- Identify and resolve data anomalies in collaboration with data engineering teams
- Translate complex, raw data into model-ready analytical datasets
- Apply statistical techniques including hypothesis testing, correlation analysis, and variance analysis
- Build, deploy, and evaluate machine learning models (regression, classification, clustering, NLP, time series)
- Design and analyze A/B experiments and causal inference studies
- Deliver data-driven insights and recommendations to business stakeholders
- Write clean, scalable, production-ready code in Python or R
- Support dashboards and self-serve analytics for decision-making
- Deploy and monitor models using MLOps best practices on cloud platforms
📊 Data Understanding & Analytical Skills
- Strong ability to quickly understand unfamiliar and complex datasets
- Experience working with messy, incomplete, or poorly documented data
- Skilled in uncovering hidden patterns, trends, seasonality, and anomalies
- Ability to challenge assumptions and ask the right questions about data
- Proficiency in data profiling, descriptive statistics, and data documentation
- Comfortable working with structured, semi-structured, and unstructured data
🛠️ Technical Skills Required
- Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) and/or R
- Strong SQL skills (DB2, SQL Server)
- Hands-on experience with Databricks for large-scale data processing and ML
- Experience with cloud platforms: Azure or AWS
- Familiarity with data warehouses and big data platforms (Databricks, Snowflake, Redshift)
- Knowledge of MLOps tools such as MLflow, Kubeflow, or Airflow
- Experience with streaming technologies like Kafka or Spark
- Solid foundation in statistics, probability, linear algebra, and experimental design
✅ Nice to Have
- Experience with deep learning, NLP, computer vision, or Bayesian methods
- Exposure to real-time or streaming data pipelines
- Open-source contributions or published research
Interested can share your resume on jsirisha@gradera.ai
Click on Apply to know more.