
Data Scientist
8 hours ago
Machines learn from experience and can perform tasks without explicit instructions.
We are seeking talented individuals to work in data science and machine learning. As a data science / ml engineer, you will collaborate closely with stakeholders across various functions to develop innovative data-driven solutions addressing diverse business challenges.
From feasibility studies to deployment, you'll be involved in the entire lifecycle—from understanding pain points to transforming data into impactful insights and scalable models.
Key Responsibilities- Collaborate with stakeholders to understand business problems and define data-driven solutions.
- Conduct feasibility studies by engaging with stakeholders to capture pain points and use cases.
- Extract and collect data from databases and other sources in collaboration with data engineers and it teams.
- Clean, preprocess, and standardize data to ensure quality and usability.
- Research appropriate solutions by reviewing literature on statistical and machine learning methodologies; explore python libraries and evaluate models (including llms).
- Perform feature engineering to build predictors essential for model accuracy.
- Code solutions using python within analytics platforms like databricks.
- Communicate findings to stakeholders and iteratively refine models based on testing and validation.
- Deploy models in analytics platforms; work with software developers on frontend designs for real-time predictions or with data visualization specialists for batch/scheduled forecasts using tableau or power bi.
- At least 2 years of experience in data science, data analytics, statistical modeling, machine learning engineering, or related roles.
- Bachelor's or master's degree in statistics, physics, computer science, engineering, mathematics, economics, or a similar field.
- Proficient in python with experience using libraries such as statsmodels, tensorflow, pytorch, etc., for statistical modeling, machine/deep learning, and handling big data.
- Knowledge of large language models (llms) for natural language processing.
- Knowledge of statistical and machine learning modeling (e.g., clustering, regression, time series).
- Experience with sql and data manipulation techniques.
- Familiarity with analytics platforms such as databricks, domino, dataiku.
- Familiarity with dashboard and visualization tools like tableau and power bi.
This role involves working with stakeholders to develop data-driven solutions.
The ideal candidate has experience in data science, data analytics, and machine learning engineering.
Willingness to work on a mid shift is an advantage.
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