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FactSet - Software Engineer III - Python/Machine Learning Job Opening In Hyderabad – Now Hiring Factset Research Systems


Job description

<p><p>Were seeking a passionate and experienced Senior Python & Machine Learning Engineer to join our Data domain team.<br/><br/> Youll work on unique, one-of-a-kind problem statements using advanced GenAI, large language models (LLMs), and modern data engineering frameworks.<br/><br/> You will help conceptualize and deliver impactful solutions that push the boundaries of data science and machine learning in finance.</p><br/><p><b>Responsibilities :</b><br/><br/></p><p>- Design, develop, and deploy sophisticated machine learning and GenAI models to solve complex data problems at scale.<br/><br/></p><p>- Implement, optimize, and scale ML solutions using Databricks, Spark, and cloud-native data ecosystems (AWS/Azure/GCP).<br/><br/></p><p>- Collaborate with other engineers, product managers, and UX teams to build robust, high-performance Python-based analytics pipelines.<br/><br/></p><p>- Develop and finetune LLMs and generative AI applications for structured and unstructured financial data.<br/><br/></p><p>- Architect data processing workflows leveraging Delta Lake, Feature Stores, and MLOps best practices.<br/><br/></p><p>- Translate cutting-edge research (papers, new ML techniques) into production solutions.<br/><br/></p><p>- Mentor junior data scientists and engineers on ML, best practices and GenAI.<br/><br/></p><p>- Work on one-of-a-kind data challenges, including entity disambiguation, real-time risk analytics, NLP, graph data modeling, and anomaly detection.<br/><br/></p><p>- Keep up-to-date with the latest in ML tooling, GenAI, Databricks, and cloud data :</b><br/><br/></p><p>- Bachelors/Masters in Computer Science, Data Science, Mathematics, or related field.<br/><br/></p><p>- 5-6 years professional experience in ML, Python programming, and data engineering.<br/><br/></p><p>- Deep expertise in Python (NumPy, Pandas, PySpark, FastAPI, etc.) and ML frameworks (TensorFlow, PyTorch, Transformers).<br/><br/></p><p>- Practical experience with GenAI: training/fine-tuning LLMs (OpenAI, HuggingFace, Google Gemini, etc.), prompt engineering, and retrieval-augmented generation (RAG).<br/><br/></p><p>- Hands-on experience with Databricks (Workspace, MLflow, Delta Lake, Notebooks).<br/><br/></p><p>- Strong knowledge of cloud data platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).<br/><br/></p><p>- Applied experience with ETL/ELT, data lakes, real-time streaming (Kafka, Spark Streaming).<br/><br/></p><p>- Proven track record of tackling cutting-edge data problems at scale published research or open source contributions a plus.<br/><br/></p><p>- Familiarity with modern MLOps toolchains (MLflow, Airflow, Feature Store, CI/CD).<br/><br/></p><p>- Effective communicator with excellent collaboration skills.</p><br/><p><b>Tech Stack :</b><br/><br/></p><p>- Python, PySpark, FastAPI, Flask.<br/><br/></p><p>- TensorFlow, PyTorch, HuggingFace Transformers.<br/><br/></p><p>- Databricks, Delta Lake, MLflow.<br/><br/></p><p>- AWS/Azure/GCP S3, Blob Storage, EC2, Lambda, Step Functions.<br/><br/></p><p>- SQL, NoSQL.</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations


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Unlock Your FactSet Software Potential: Insight & Career Growth Guide


Real-time FactSet Software Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for FactSet Software in Hyderabad, India, highlighting market share and opportunities for professionals in FactSet Software roles.

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Are You Looking for FactSet Software Engineer III Python/Machine Learning Job?

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Factset Research Systems adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying India laws and regulations

What Is the Average Salary Range for FactSet Software Engineer III Python/Machine Learning Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Hyderabad. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for FactSet Software Engineer III Python/Machine Learning?

Key qualifications for FactSet Software Engineer III Python/Machine Learning typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for FactSet Software Engineer III Python/Machine Learning Job Success

Factset Research Systems interview tips for FactSet   Software Engineer III   Python/Machine Learning

Here are some tips to help you prepare for and ace your FactSet Software Engineer III Python/Machine Learning job interview:

Before the Interview:

Research: Learn about the Factset Research Systems's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your FactSet Software Engineer III Python/Machine Learning interview at Factset Research Systems, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Factset Research Systems's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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