<p><p><b>Role Overview :</b></p><p><p><b><br/></b></p>We are seeking a highly skilled Data Scientist with 3 - 4 years of experience in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning.
The ideal candidate will be responsible for building, deploying, and optimizing predictive models across domains such as regression, anomaly detection, natural language processing (NLP), and industrial analytics (predictive maintenance).</p><p><br/>You will collaborate with cross-functional teams including product, engineering, and domain experts to design scalable pipelines, drive business insights, and deliver innovative AI-powered solutions that create measurable business impact.</p><p><br/></p><p><b>Key Responsibilities :</b></p><p><p><b><br/></b></p>- Design, develop, and deploy AI/ML and Deep Learning models for regression, classification, clustering, anomaly detection, and time-series forecasting.<br/><br/></p><p>- Apply advanced neural architectures such as CNNs, RNNs, LSTMs, Transformers, and Autoencoders to solve real-world business problems.<br/><br/></p><p>- Implement Natural Language Processing (NLP) techniques, including BERT, GPT-based models, embeddings, semantic similarity, and topic modeling.<br/><br/></p><p>- Build and maintain predictive analytics pipelines for industrial/manufacturing use cases, especially predictive maintenance.<br/><br/></p><p>- Conduct Exploratory Data Analysis (EDA), feature engineering, data preprocessing, and statistical validation to ensure robust model performance.<br/><br/></p><p>- Collaborate with data engineers to design scalable data pipelines and ensure seamless integration of ML models into production systems.<br/><br/></p><p>- Communicate findings and insights to stakeholders through clear visualizations, dashboards, and reports.<br/><br/></p><p>- Stay updated with the latest research and advancements in AI/ML, and recommend adoption of new methods where Skills & Qualifications :</b></p><p><b><br/></b></p><p><b>- Programming & Tools : </b> Strong proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Experience : </b> 34 years of hands-on experience in AI/ML and Deep Learning model development, deployment, and Deep Learning Expertise : </b> Solid knowledge of CNNs, RNNs, LSTMs, Transformer-based NLP Knowledge : </b> Practical experience with modern NLP models (e.g., BERT, GPT, embeddings, text classification, sentiment Statistical Foundation : </b> Strong background in probability, hypothesis testing, statistical inference, and mathematical Database & Data Handling : </b> Experience with SQL and databases (PostgreSQL, InfluxDB, or similar) for data extraction, transformation, and Problem-Solving Mindset : </b> Ability to translate complex business challenges into data-driven solutions.</p><p><br/></p>- Collaboration : Strong communication skills with the ability to work in a cross-functional Skills (Nice to Have) : </b></p><p><br/></p><p>- Experience in MLOps frameworks (MLflow, Kubeflow, Airflow).</p><p><br/></p>- Familiarity with cloud platforms (AWS, GCP, or Azure).<br/><br/></p><p>- Exposure to big data tools (Spark, Hadoop).<br/><br/></p><p>- Prior work in industrial/manufacturing analytics or IoT data.<br/><br/></p><p>- Knowledge of data visualization tools (Power BI, Tableau, Plotly).</p><br/></p> (ref:hirist.tech)