Data Engineer/Scientist - Machine Learning/Python
First seen by Alion on Aug 20, 2026.
Job Description :
Must Have Skills :
Python, SQL, Statistics, Probability, Pandas, NumPy, Scikit-learn, Exploratory Data Analysis (EDA), Data Cleaning, Feature Engineering, Hypothesis Testing, A/B Testing, Regression, Classification, Clustering, Time Series Analysis, Data Visualization, Matplotlib, Business Problem Solving, Model Evaluation, Communication Skills.
Good To Have Skills :
PyTorch, TensorFlow, XGBoost, LightGBM, NLP, Generative AI, Large Language Models (LLMs), Tableau, Power BI, Spark, Databricks, Snowflake, BigQuery, AWS, Microsoft Azure, Google Cloud Platform (GCP), MLflow, Causal Inference, Recommendation Systems, Optimization.
Experience Requirement : 2 yrs to 10 Yrs
Work Mode : From Office
Job Role : Full Time
Education :
B.E., B.Tech, M.Tech, MCA, M.Sc (Computer Science, Information Technology, Artificial Intelligence, Data Science) or equivalent practical experience
Shift Timings : 9.30 Am - 6.30 Pm
Key Requirements :
- Hands-on experience in Data Science, Machine Learning, Predictive Analytics.
- Strong proficiency in Python, including experience with data manipulation, statistical analysis, machine learning, and model development using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch and related frameworks.
- Solid understanding of statistics, probability theory, hypothesis testing, regression analysis, sampling techniques, and experimental design to support data driven decision making.
- Apply statistical and machine learning techniques to analyze large datasets, identify patterns, build predictive models, and generate actionable business insights.
- Experience in building REST APIs and integrating AI models into production environments.
- Strong understanding of statistics, machine learning algorithms, forecasting techniques, and optimization methods.
- Excellent analytical, problem-solving, and communication skills with the ability to work in cross-functional teams.
Good To Have :
- Experience with Generative AI technologies, Large Language Models (LLMs).
- Experience working with SQL and NoSQL databases, data warehouses, and big data technologies.
- Familiarity with cloud platforms such as AWS, and containerization technologies such as Docker and Kubernetes.
Roles & Responsibilities :
- Collaborate with business stakeholders, product managers, and engineering teams to translate business requirements into analytical solutions.
- Extract and integrate data from multiple sources through APIs, databases, and file-based interfaces.
- Analyze structured and unstructured data to identify trends, patterns, and actionable business insights.
- Perform data preprocessing, feature engineering, model development, deployment and model evaluation.
- Evaluate, fine-tune, and optimize AI/ML models to improve accuracy, performance, scalability, and reliability.
- Develop APIs and services for model deployment and integration with enterprise systems.
- Ensure data quality, governance, security, and compliance throughout the analytics lifecycle.
- Stay current with emerging AI, GenAI, machine learning, and data science technologies and recommend their adoption where appropriate.
Skills
Data Science, Python, Machine Learning, Data Engineering, Predictive Analytics, Pandas, Numpy, LLM