Data Science Specialist - NLP/Machine Learning Acsia Technologies

4.0 - 8.0 years

0 Lacs

thiruvananthapuram, kerala

On-site

You are a Data Science Specialist with 4-5 years of experience in designing and implementing advanced analytical solutions. You should have a strong foundation in statistics and expertise in solving real-world business problems using Machine Learning and Data Science. Your track record should include building and deploying data products, and any exposure to NLP and Generative AI will be considered an advantage. Your key responsibilities will include collaborating with cross-functional teams to translate business problems into data science use cases, designing, developing, and deploying data science models, building and productionizing data products for measurable business impact, performing exploratory data analysis, feature engineering, model validation, and performance tuning, as well as applying statistical methods to uncover trends, anomalies, and actionable insights. You will need to implement scalable solutions using Python (or R/Scala), SQL, and modern data science libraries. It is important to stay updated with advancements in NLP and Generative AI and evaluate their relevance to internal use cases. Additionally, you should be able to communicate findings and recommendations clearly to both technical and non-technical stakeholders. Qualifications: - Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, Engineering, or a related discipline is required. - A Master's degree or certifications in Data Science, Machine Learning, or Applied Statistics is a strong advantage. Experience: - 4-5 years of hands-on experience in data science projects across different domains. - Demonstrated experience in end-to-end ML model development, from problem framing to deployment. - Prior experience working with cross-functional business teams is highly desirable. Must-Have Skills: - Statistical Expertise: Strong understanding of hypothesis testing, regression, classification techniques, and distributions. - Business Problem Solving: Ability to translate ambiguous business challenges into data science use cases. - Model Development: Hands-on experience in building and validating machine learning models. - Programming Proficiency: Strong skills in Python (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn), and SQL. - Data Manipulation: Experience in handling structured/unstructured datasets, EDA, and data cleaning. - Communication: Ability to explain technical concepts to non-technical audiences. - Version Control & Collaboration: Familiarity with Git/GitHub and collaborative practices. - Deployment Mindset: Understanding how to build usable and scalable data products. Desirable Skills: - Experience with survival analysis or time-to-event modeling techniques. - Exposure to NLP methods like tokenization, embeddings, sentiment analysis. - Familiarity with Generative AI technologies like LLMs, transformers, prompt engineering. - Experience with MLOps tools, pipeline orchestration, or cloud platforms (AWS, GCP, Azure).,

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