Posted on: 18/07/2025
Role : Data Scientist
Location : @Pune , india
Experience : 2+ years
NOTE : Immediate joiner
Job Summary :
We are looking for a highly skilled and experienced Data Scientist to join our growing analytics team. As a Data Scientist, you will be responsible for extracting insights from large, complex datasets, building predictive and prescriptive models, and helping to drive data-driven decisions across the organization. You will work closely with cross-functional teams to design experiments, prototype solutions, and implement algorithms that have a tangible impact on the business.
Key Responsibilities :
Data Exploration & Analysis :
- Perform exploratory data analysis using statistical techniques and visualization tools.
- Analyze structured and unstructured data from multiple sources (databases, APIs, flat files, etc.).
Model Development :
- Optimize model performance using feature engineering, hyperparameter tuning, and model selection techniques.
- Use ML Ops tools for model deployment and monitoring in production environments.
Business & Stakeholder Collaboration :
- Collaborate with business stakeholders, analysts, engineers, and product teams to gather requirements and present findings.
- Translate complex analytical concepts into business-friendly language.
- Support experimentation and A/B testing frameworks.
Data Engineering Support :
- Write efficient, reusable, and modular code in Python, SQL, or Spark.
- Assist in creating and maintaining data lakes, feature stores, or model registries.
Documentation & Reporting :
- Create dashboards and reports to communicate key insights to stakeholders.
Required Skills & Qualifications :
- Bachelors/Masters/Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or related field.
- 2-3 years of hands-on experience in a data science or machine learning role.
- Proficiency in Python or R, and SQL. Experience with frameworks like scikit-learn, TensorFlow, PyTorch, or XGBoost.
- Strong grasp of statistical modeling, hypothesis testing, and machine learning algorithms.
- Experience with data wrangling using tools like Pandas, Spark, or Dask.
- Exposure to cloud platforms like AWS, GCP, or Azure.
- Familiarity with version control (Git), CI/CD, and containerization (Docker) is a plus.
- Excellent problem-solving and communication skills.
Preferred Qualifications :
- Experience with time-series forecasting, natural language processing, or computer vision.
- Understanding of big data platforms (Hadoop, Hive, Presto).
- Knowledge of ML Ops frameworks like MLflow, Kubeflow, or SageMaker.
- Prior experience in domains like retail, finance, healthcare, automobile, or marketing analytics.
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