Talent Acquisition at Tredence Analytics
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Tredence - Senior Data Scientist - Forecasting/NLP/LLM/GenAI/Markdown Optimization (5-8 yrs)
Tredence is a global analytics services and solutions company. We are one of the fastest growing private companies in the country for three straight years according to the Inc. 5000 and we continue to set ourselves apart from our competitors by attracting the greatest talent in the data analytics and data science space. Our capabilities range from Data Visualization, Data Management to Advanced analytics, Big Data and Machine Learning. Our uniqueness is in building Scalable Big Data Solutions on Onprem/GCP/Azure cloud in a very cost effective and easily scalable manner for our clients. We also come in with some strong IP and pre-built analytics solutions in data mining, BI and Big Data.
Roles and Responsibilities:
As a, Associate Manager - Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve predefined outcomes.
- Engage with clients to understand current and future business goals and translate business problems into analytical frameworks
- Develop custom models based on in-depth understanding of underlying data, data structures, and business problems to ensure deliverables meet client needs
- Create repeatable, interpretable and scalable models
- Effectively communicate the analytics approach and insights to a larger business audience
- Collaborate with team members, peers and leadership at Tredence and client companies
1. Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience.
2. 5+ years of experience in data science, building hands-on ML models
3. Experience leading the end-to-end design, development, and deployment of predictive modeling solutions.
4. Excellent programming skills in Python. Strong working knowledge of Python's numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc. 5. Advanced SQL skills with SQL Server and Spark experience.
6. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks
7. Experience with Natural Language Processing (NLTK) and text analytics for information extraction, parsing and topic modeling. 8. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills. Thrive in a fast-paced, innovative environment 9. Experience with data visualization tools - PowerBI, Tableau, R Shiny, etc. preferred
10. Experience with cloud platforms such as Azure, AWS is preferred but not required