Data Scientist - Machine Learning Algorithm

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