Data Scientist with Predictive Modeling / ML

Overview

Hybrid
$140,000 - $160,000
Full Time

Skills

Machine Learning (ML)
Pandas
SQL
Python
Algorithms
Predictive Modeling
Predictive Modelling
Microsoft Azure
Databricks
Apache Spark
Tableau
Science
MatLab

Job Details

Responsibilities

  • Perform data mining, exploration, and analysis to uncover drivers, trends, and business opportunities

  • Build predictive models end-to-end: data prep, feature engineering, model selection, training, tuning, and evaluation

  • Design, train, evaluate, and implement machine learning algorithms for forecasting, prediction, and decision support

  • Partner with business stakeholders to identify pain points and translate requirements into analytics-enabled solutions

  • Develop and maintain KPIs, metrics, trend tracking, and forecasting frameworks tied to business outcomes

  • Produce clear visualizations and storytelling (e.g., Tableau) to communicate insights and recommendations

  • Work closely with the team across the full project lifecycle: requirements design development testing/evaluation demo deployment

  • Coordinate with data engineering to scale and deploy models + pipelines into production within Azure/Databricks

  • Troubleshoot model performance, drift, data quality issues, and continuously improve deployed solutions

  • Maintain documentation, share learnings, and contribute to repeatable processes and standards

Must-Have Skills

  • Bachelor s degree in Data Science / Analytics (or related) or equivalent practical experience

  • 2+ years hands-on experience in predictive modeling and machine learning

  • Strong Python + SQL skills (data extraction, transformation, analysis, and modeling workflows)

  • Practical experience with core data science libraries/toolkits:

    • NumPy, Pandas (data prep, feature engineering, analysis)

    • Familiarity with tools like MatLab (as applicable)

  • Experience working in Azure and Databricks environments (notebooks, Spark workflows, data access patterns)

  • Understanding of model evaluation techniques (e.g., train/test splits, cross-validation, accuracy/precision/recall/AUC, error metrics, etc.)

  • Ability to work cross-functionally and communicate technical results to non-technical stakeholders

  • Strong working style: team-oriented, organized, problem-solver, detail-focused

  • English proficiency sufficient for workplace safety and job execution

    Regards
    Rohit

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