
Data Scientist
2 weeks ago
Role Overview :
As a Data Scientist, you will be a hands-on expert in the entire data science lifecycle.
You will be responsible for identifying business problems, collecting and cleaning data, building and validating models, and deploying them to production.
You will work closely with engineering, product, and business teams to ensure that our data solutions deliver tangible value.
Key Responsibilities :
- Collaborate with business and product teams to define and frame data-driven problems.
- Collect, clean, and preprocess large, complex datasets from various sources.
- Design and implement machine learning models, algorithms, and predictive analytics to solve business challenges.
- Conduct exploratory data analysis to uncover trends, patterns, and insights.
- Develop and implement data pipelines for model training and serving.
- Deploy and monitor machine learning models in production environments, ensuring their performance and reliability.
- Communicate complex findings and insights to technical and non-technical stakeholders through clear visualizations and presentations.
- Stay updated with the latest research and advancements in the fields of data science, machine learning, and AI.
- Contribute to the continuous improvement of our data science methodologies and infrastructure.
Required Skills & Qualifications:
- Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.
- 6+ years of professional experience as a Data Scientist.
- Strong proficiency in programming languages like Python or R.
- Extensive experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
- Deep understanding of machine learning algorithms, statistical modeling, and experimental design.
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) is a plus.
- Proficiency in SQL for data extraction and manipulation.
- Familiarity with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, or GCP).
- Experience with MLOps principles and tools (e.g., MLflow, Kubeflow).
- Excellent analytical, problem-solving, and communication skills.
Nice to Have :
- Experience with natural language processing (NLP) or computer vision.
- Knowledge of data visualization tools like Tableau or Power BI.
- Prior experience in a consulting or B2B environment.
- Experience with building and deploying Generative AI or LLM-based applications
(ref:hirist.tech)
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