Overview
We are looking for a proactive and analytical Data Scientist to join our growing team. The ideal candidate will be deeply passionate about working with data, possess a strong foundation in statistical analysis and machine learning, and demonstrate the ability to derive actionable insights from complex datasets. This role requires experience in data wrangling, exploratory data analysis (EDA), and hands-on implementation of data science techniques, including Natural Language Processing (NLP).
Responsibilities
- Collect, clean, and organize structured and unstructured data from diverse sources.
- Ensure data accuracy, consistency, and readiness for analysis.
- Perform thorough EDA to understand data distributions, relationships, and anomalies.
- Use visualization tools (e.g., Matplotlib, Seaborn, Pandas) to communicate findings.
- Work closely with business teams to identify trends and patterns that guide decisions.
- Handle missing data, outliers, and normalization techniques effectively.
- Transform raw data into features suitable for modeling and insights.
- Automate and optimize data preparation pipelines.
- Develop NLP pipelines for text classification, sentiment analysis, named entity recognition, and more.
- Work with tools such as NLTK, Hugging Face Transformers, and BERT-based models.
- Analyze and process unstructured text data for business use cases.
- Translate complex data problems into clear, actionable insights.
- Proactively identify opportunities for data-driven improvements across departments.
- Conduct root cause analysis and support hypothesis-driven investigations.
- Work closely with cross-functional teams including data engineers, analysts, and product stakeholders.
- Exhibit a high level of accountability, ownership, and willingness to support teammates.
Qualifications
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
- 2–3 years of experience in a data science role.
- Proficiency in Python (NumPy, Pandas, Scikit-learn), SQL and MongoDB
- Hands-on experience with NLP frameworks such as NLTK, or Hugging Face.
- Solid understanding of machine learning algorithms and data modeling techniques.
- Strong data visualization and storytelling skills.
- Excellent problem-solving and critical thinking abilities.
- Strong communication skills and a collaborative mindset.
