Data Scientist

QAP Software Solutions

0 years

0 Lacs

bengaluru karnataka india

Posted:1 day ago| Platform:

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Skills Required

data engagement engineering forecasting learning processing design support programming development python pyspark sql aggregations git github spark databricks management configuration versioning transactions pipeline etl orchestration yaml ml mlflow tracking model deployment analysis profiling code testing integration docker containerization monitoring logging collaboration communication adaptability

Work Mode

Remote

Job Type

Contractual

Job Description

Location: Remote.

Immediate Joiner

Role Overview

We require a Data Scientist on loan staff engagement with strong expertise in data engineering, time series forecasting, machine learning frameworks, and large-scale data processing. The resource will work with internal teams to design, develop, and deploy data science solutions to support business- critical use cases.

Core Technical Skills Programming & Development

Python (advanced) – pandas, PySpark, data manipulation
SQL (advanced) – complex queries, window functions, aggregations
Git/GitHub – branching, pull requests, CI/CD
Spark/PySpark – distributed data processing, DataFrames, transformations

Data Engineering & Platforms

Databricks – workspace management, cluster configuration, notebooks
Delta Lake – data versioning, ACID transactions, time travel
Data Pipeline Development – ETL/ELT processes, orchestration
YAML/Configuration Management – parameterized, flexible workflows

ML / Data Science

MLflow – experiment tracking, model versioning, deployment
Feature Engineering – time series features, aggregations, transformations
Time Series Analysis – forecasting, seasonality, trend analysis
Data Quality & Validation – profiling, anomaly/outlier detection
OOP & Configuration-Driven Development – reusable, modular code design
Testing – unit tests, integration tests, validation frameworks

Additional Valuable Skills

Docker/Containerization – reproducible deployments
Monitoring & Logging – observability of data pipelines and ML models

Soft Skills & Behavioral Competencies

Problem-Solving: Ability to frame and solve business problems analytically
Collaboration: Works effectively with cross-functional teams (engineering, product, business)
Communication: Clear in presenting insights and technical details to stakeholders
Ownership & Accountability: Delivers tasks end-to-end with minimal supervision
Adaptability: Thrives in fast-paced, evolving project environments
Continuous Learning: Keeps up with new ML/data tools and practices

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