Job Title: Data Scientist (Product & Algorithms)
Location: Delhi (Hybrid/Remote)
Job Type: Full-time
About Us At Best Nanotech, we are on a mission to [insert mission]. We generate massive amounts of data every day, but data without insight is just overhead. We are building a high-performance Data Science team to help us make smarter, faster decisions.
The Role We are looking for a Data Scientist who sits at the intersection of coding, statistics, and business strategy.
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You won't just be handed a ticket to build a model. You will partner with Product Managers and Engineers to identify problems, formulate hypotheses, and prototype solutions that scale.
Key Responsibilities
- Exploratory Analysis: Mine large datasets to uncover trends, patterns, and user behaviors that drive product innovation.
- Modeling: Build and validate predictive models (Regression, Classification, Clustering) using Python (Scikit-Learn/Pandas).
- Experimentation: Design, execute, and analyze A/B tests to validate product changes.
- Data Wrangling: Write complex SQL queries to extract data and build lightweight ETL pipelines for your analysis.
- Storytelling: Visualize your findings (using Tableau, Looker, or Matplotlib) and present actionable recommendations to stakeholders.
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What You Bring (Requirements)
- Experience: 3+ years of experience in a Data Science or Analytics role.
- Education: Degree in Math, Statistics, Computer Science, Economics, or related quantitative field.
- The Toolkit:
- Expert-level SQL (Joins, Window Functions, CTEs).
- Strong proficiency in Python (preferred) or R.
- Experience with libraries like Pandas, NumPy, Scikit-learn.
- The Math: Solid grasp of statistics (Hypothesis testing, distributions, bias/variance).
- The Soft Skills: Ability to translate complex technical results into plain English for non-technical partners.
Bonus Points
- Experience with Cloud Data Warehouses (Snowflake, BigQuery).
- Experience deploying models as APIs (Flask/FastAPI).
- Familiarity with causal inference techniques.
How to Apply Click Easy Apply or send your portfolio/GitHub link to [email address].
