Python Developer at OnActive · Remote only · 5 - 8 years · ₹8L - ₹10L / yr · Bootstrapped · Remote only · Posted 16 Nov 2024

bout the Role
We are seeking an experienced Python Data Engineer with a strong foundation in API and basic UI development. This role is essential for advancing our analytics capabilities for AI products, helping us gain deeper insights into product performance and driving data-backed improvements. If you have a background in AI/ML, familiarity with large language models (LLMs), and a solid grasp of Python libraries for AI, we’d like to connect!
Key Responsibilities
• Develop Analytics Framework: Build a comprehensive analytics framework to evaluate and monitor AI product performance and business value.
• Define KPIs with Stakeholders: Collaborate with key stakeholders to establish and measure KPIs that gauge AI product maturity and impact.
• Data Analysis for Actionable Insights: Dive into complex data sets to identify patterns and provide actionable insights to support product improvements.
• Data Collection & Processing: Lead data collection, cleaning, and processing to ensure high-quality, actionable data for analysis.
• Clear Reporting of Findings: Present findings to stakeholders in a clear, concise manner, emphasizing actionable insights.
Required Skills
• Technical Skills:
o Proficiency in Python, including experience with key AI/ML libraries.
o Basic knowledge of UI and API development.
o Understanding of large language models (LLMs) and experience using them effectively.
• Analytical & Communication Skills:
o Strong problem-solving skills to address complex, ambiguous challenges.
o Ability to translate data insights into understandable reports for non-technical stakeholders.
o Knowledge of machine learning algorithms and frameworks to assess AI product effectiveness.
o Experience in statistical methods to interpret data and build metrics frameworks.
o Skilled in quantitative analysis to drive actionable insights.

About OnActive
About
Similar jobs (10)
Location - Bangalore / Pune
Exp - 4 to 10 years
Required
· 3–8 years of relevant experience in data science, AI engineering, or applied machine learning roles.
· Bachelor’s or master’s degree in computer science, Mathematics, Engineering, or a related quantitative field.
· System design: ability to design scalable, reliable, and maintainable systems, including service decomposition, APIs, caching, queues and event-driven architectures, and the trade-offs between latency, throughput, cost, and consistency.
· Strong foundation in data structures and algorithms, with the ability to analyse time and space complexity and choose efficient approaches for large-scale data processing.
· Experience building and operating data-intensive or data-driven applications, such as large-scale data pipelines, batch and streaming processing, or applications whose core features depend on high-volume data.
· Strong hands-on experience in Python.
· Solid foundation in machine learning, NLP, and statistical modeling, including data exploration and visualization.
· Hands-on experience or projects involving LLMs, LangChain, LangGraph, RAG, or agentic AI systems.
· Experience delivering AI/ML solutions into production environments.
· Understanding of text processing and unstructured data.
· Knowledge of software engineering best practices (TDD, refactoring, modular design, version control).
· System design: ability to design scalable, reliable, and maintainable systems, including service decomposition, APIs, caching, queues and event-driven architectures, and the trade-offs between latency, throughput, cost, and consistency.
· Strong foundation in data structures and algorithms, with the ability to analyze time and space complexity and choose efficient approaches for large-scale data processing.
· Experience building and operating data-intensive or data-driven applications, such as large-scale data pipelines, batch and streaming processing, or applications whose core features depend on high-volume data.
· Strong analytical, problem-solving, and communication skills.
· Self-motivated, proactive, and delivery-oriented mindset.
Key Responsibilities
Strong understanding of Machine Learning algorithms (supervised and unsupervised)
Hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, or similar)
Experience in NLP techniques and libraries (NLTK, spaCy, Hugging Face, etc.)
Solid knowledge of Statistics, probability, and data analysis methods
Proficiency in SQL for querying relational databases
Strong programming skills in Python (or similar languages)
Excellent communication skills with the ability to explain complex concepts simply
Required Qualifications
3+ years of hands-on experience as a Data Scientist or in a similar role.
Strong expertise in classical machine learning and regression modeling.
Solid understanding of statistics, including probability, distributions, hypothesis testing,
and correlation analysis.
Proficiency in Python with libraries such as: scikit-learn pandas NumPy
Experience working with structured/tabular data.
Strong problem-solving and analytical thinking skills.
Ability to clearly explain models and results to non-technical stakeholders.
Role Overview
As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact.
Key Responsibilities
Data Science & Machine Learning
- Analyze structured and unstructured data to identify patterns, trends, and business opportunities.
- Perform exploratory data analysis (EDA), feature engineering, and data preparation.
- Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.
- Apply statistical techniques to solve business problems and validate model performance.
- Design and execute experiments to improve model accuracy and business outcomes.
AI Solution Development
- Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.
- Translate business requirements into scalable data science approaches.
- Contribute to Generative AI and advanced analytics initiatives where applicable.
- Document methodologies, model performance, and key findings.
Required Technical Skills
- Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.
- Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.
- Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.
- Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.
- Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.
- Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.
- Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.
- Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.
- Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 2–4 years of experience developing machine learning or data science solutions.
- Experience working on end-to-end data science projects in a business environment.
Nice to Have
- Exposure to Generative AI, LLMs, RAG, or Agentic AI.
- Experience with Computer Vision or Natural Language Processing (NLP).
- Familiarity with cloud-based AI platforms.
- Knowledge of construction, engineering, manufacturing, or industrial domains.
- Participation in hackathons, research, Kaggle competitions, or open-source projects.
Soft Skills
Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.
🚀 We’re Hiring | Data Scientist 🧠📊
Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!
🔹 Experience: 8+ Years
🔹 Must-Have Skills:
🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization
📍 Location: Pune
💼 Work Mode: Work from Office
If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!
📩 Interested? Kindly text
#Hiring #DataScientist #DataScience #MachineLearning #Python #NLP #AI #Cloud #DataVisualization #TechJobs #HiringNow
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Data Science Engineer – Python, SQL, Statistics & Machine Learning
Company: Talview
Experience: 3–5 years
Location: Bengaluru, Karnataka
Work Mode: Work from Office, with some flexibility
Work Week: 5 days
About Talview
Talview builds AI-powered hiring and assessment solutions for enterprise organisations. Our products support candidate screening, interview scheduling and online exam proctoring, helping teams improve efficiency and make better-informed decisions.
Role Overview
We are looking for a Data Science Engineer with strong hands-on experience in Python, SQL, statistics and classical machine learning, along with experience working on GenAI and Large Language Models (LLMs).
You will work across data processing, statistical analysis, experimentation, model development, evaluation and production AI/ML workflows. You will collaborate with Engineering and Product teams to translate business problems into measurable data science solutions.
This role requires practical experience in classical ML and statistics, beyond working only with LLM APIs or prompt engineering.
Roles and Responsibilities
- Develop complex SQL queries for data extraction, transformation, analysis and validation.
- Use Python for data processing, exploratory data analysis, automation and reusable experimentation utilities.
- Apply statistical analysis, hypothesis testing and experimental design to evaluate business and product outcomes.
- Develop and evaluate machine learning models using appropriate metrics and clearly defined success criteria.
- Build LLM workflows involving prompting, structured outputs and comparative evaluation of models and configurations.
- Create evaluation datasets, benchmarks, sampling strategies and ground-truth validation approaches.
- Perform error analysis and root-cause analysis to identify model failures, anomalies and performance degradation.
- Analyse production data and troubleshoot data, model and pipeline issues.
- Integrate data from APIs, databases and other structured and unstructured sources.
- Collaborate with Engineering and Product teams on ML pipelines, evaluation frameworks and inference workflows.
- Research and test techniques to improve AI/ML system performance.
Required Skills and Experience
- 3–5 years of relevant experience in Data Science, Machine Learning, AI or a related field.
- Strong hands-on Python programming skills.
- Strong SQL skills for complex querying, data transformation and analysis.
- Solid understanding of statistics, hypothesis testing, experiment design and performance measurement.
- Practical experience developing and evaluating classical machine learning models.
- Experience with LLMs, prompting, structured outputs and evaluation.
- Experience defining evaluation metrics, benchmarks and error-analysis approaches.
- Ability to work with APIs, databases and structured and unstructured datasets.
- Strong analytical and problem-solving skills.
- Ability to explain technical decisions, interpret results and communicate findings to stakeholders.
Preferred Skills
- Experience designing end-to-end ML or LLM workflows.
- Experience with dataset creation, sampling, annotation and ground-truth validation.
- Experience analysing production AI/ML systems and debugging model or pipeline issues.
- Experience building reusable experimentation and evaluation frameworks.
Key Skills
Python, SQL, Data Science, Statistics, Machine Learning, Classical ML, Hypothesis Testing, Experimental Design, Model Evaluation, Exploratory Data Analysis, GenAI, Large Language Models, LLM Evaluation, Error Analysis
1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Job Description: Python + AI
Company: Wissen Technology
Location: Bangalore, India
Experience: 5+Years
Employment Type: Full-Time
Role: Python + AI / Data Engineer
About the Role
Wissen Technology is looking for experienced Python + AI / Data Engineering professionals to join our technology team in Bangalore. The ideal candidate will have strong hands-on experience in Python, Artificial Intelligence, Generative AI, PySpark, Snowflake, and data pipeline development.
The candidate should be capable of designing and developing scalable data and AI solutions, building robust ETL/ELT pipelines, working with large datasets, and integrating AI/ML capabilities into enterprise applications.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python and PySpark.
- Develop robust ETL/ELT pipelines for processing large volumes of structured and unstructured data.
- Build and optimize data processing solutions using Apache Spark / PySpark.
- Develop data ingestion and transformation pipelines into Snowflake.
- Design and implement scalable Snowflake data models, tables, views, and SQL transformations.
- Work with batch and, where applicable, real-time data processing pipelines.
- Build and integrate AI and Generative AI solutions using Python.
- Develop LLM-based applications, RAG solutions, AI agents, and AI-powered services.
- Integrate AI models with enterprise data platforms and data pipelines.
- Develop REST APIs and microservices using FastAPI, Flask, or Django.
- Perform data cleansing, transformation, validation, and quality checks.
- Optimize PySpark jobs, SQL queries, Snowflake workloads, and data pipelines for performance and scalability.
- Implement data pipeline monitoring, logging, error handling, and alerting.
- Work with cloud platforms such as AWS, Azure, or GCP.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders.
- Participate in technical design, architecture, code reviews, and production support.
- Mentor junior engineers and contribute to engineering best practices.
Preferred Qualifications
- Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, or a related field.
- Experience working on enterprise-scale AI and data engineering projects.
- Experience combining Python + PySpark + Snowflake + AI/GenAI in production environments.
- Experience with Databricks is an advantage.
- Experience with AI Agents / Agentic AI and tool/function calling.
- Knowledge of distributed systems and cloud-native architecture.
- Experience leading technical initiatives or mentoring engineering teams.
Data Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
role: data engineer
Python pyspark, SQL, data engineer
5+yrs
Bangalore/Hyderabad
immediate to 15days.









