Data Science Engineer
- Esuccess Ai
- 0 - 1 years
- Noida, Gurugram
- 4 months ago
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Job Description
Data Science Engineer
Experience : 0-1 Year
Job Location : Noida (Onsite)
About Role
As a data scientist, you will extract, analyse and interpret large volumes of data from various sources, using algorithms, data mining, AI, machine learning, and statistical tools to make it accessible and useful for businesses. Once you have interpreted the data, you will present your findings in clear, engaging, and actionable formats.
You'll use your technical, analytical and communication skills to collect and examine data, helping organisations identify patterns and solve problems. This might involve predicting customer behaviour or addressing environmental challenges such as plastic pollution.
Requirements
Education Qualification
Bachelors / Masters Degree in a Data Science/ Artificial Intelligence/ Computational Mathematics/ Statistics or related field. Technical Skills
1. Programming & Scripting
- Python: Essential, with libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch.
- SQL: Key for querying structured datasets.
- Version Control: Git for reproducibility.
- Visualization Tools: Matplotlib, Seaborn; also BI tools like Tableau, Power BI
2. Data Handling & Processing
- Data Wrangling: Cleaning, transforming, and merging large datasets efficiently.
- Databases: Comfortable with relational (PostgreSQL, MySQL) and non-relational (MongoDB, DynamoDB) systems.
- ETL/ELT Pipelines: Experience with tools like Airflow, dbt, or Luigi for automated workflows.
- Exploratory Data Analysis (EDA): Investigative analysis with visualization (Matplotlib, Seaborn).
3. Statistical & Mathematical Foundations
- Statistics & Probability: Hypothesis testing, A/B tests, sampling, Bayesian inference.
- Linear Algebra & Calculus: Necessary for model optimization (gradient descent, matrix operations).
4. Machine Learning & Modeling
- Core ML Algorithms: Regression, classification, clustering, ensembles using Scikit-learn.
- Training & Evaluation: Cross-validation, hyperparameter tuning, metrics for regression/classification.
- Deployment Readiness: Knowledge of overfitting prevention, model interpretability, and monitoring.
5. Feature Engineering & Model Evaluation
- Feature Engineering: Creating relevant predictive features (e.g., price per unit, age of asset).
- Model Evaluation & Selection: Choosing algorithms, tuning hyperparameters, validating model quality
Responsibilities
- Partner with product managers, analysts, and business teams to translate requirements into technical solutions.
- Present results to stakeholders in a clear, non-technical manner.
- Recommend actionable strategies based on analysis.
- Help define success metrics for data science projects.
- Participate in code reviews and share best practices with junior team members.
- Build algorithms and design experiments to merge, manage, interrogate and extract data for tailored reporting
- Communicate complex data insights clearly and effectively to both technical and non-technical audiences
- Create compelling reports that tell the story of how customers or clients interact with a business
- Stay informed about emerging technologies and methodologies
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full timeContact Details:
Company: Esuccess AiLocation(s): Noida, Gurugram
Keyskills: Postgres Database Programming Machine Learning Algorithms Data Analytics Python
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