Data Scientist

About the Role

Data Scientist with 5+ years of hands-on expertise

Key Responsibilities

• Design, develop, and deploy

  end-to-end data science and machine learning solutions

  .
• Perform advanced data analysis,

  exploratory data analysis (EDA)

  , and feature engineering on large datasets.
• Build, train, tune, and optimize

  predictive, classification, clustering, and forecasting models

  .
• Analyze business datasets to identify

  trends, patterns, anomalies, and actionable insights

  .
• Collaborate closely with business stakeholders to translate analytical findings into

  data-driven strategies and recommendations

  .
• Work with data engineers to ensure

  scalable, reliable, and production-ready data pipelines

  .
• Utilize

  Databricks

  for large-scale data processing, collaborative analytics, and ML workflows.
• Work with

  Snowflake

  for cloud-based data warehousing, analytics, and optimized data access.
• Develop dashboards, reports, or analytical summaries to support

  leadership and operational decision-making

  when required.
• Communicate insights, model performance, risks, and recommendations to

  technical and non-technical audiences

  .
• Monitor model performance, manage

  data and model drift

  , and continuously improve deployed solutions.
• Mentor junior team members and contribute to

  data science standards, best practices, and reusable frameworks

  .
• Prepare and maintain

  technical documentation

  for models, methodologies, pipelines, and analytical insights.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in

  Data Science, Computer Science, Statistics, Mathematics

  , or a related field.

• 5+ years of professional experience

  in data science, applied machine learning, or advanced analytics roles.
• Strong proficiency in

  Python

  (NumPy, Pandas, Scikit-learn, Statsmodels).
• Hands-on experience with

  machine learning algorithms

  (regression, classification, clustering, time series).
• Strong command of

  SQL

  for data extraction, transformation, and analysis.
• Solid understanding of

  statistics, probability, hypothesis testing, and experimental analysis

  .
• Proven experience performing

  EDA, data validation, and data quality checks

  on large datasets.
• Ability to derive

  business insights

  from data and present them clearly using visualizations.
• Experience with data visualization and reporting tools (

  Matplotlib, Seaborn, Plotly, Power BI, Tableau

  ).
• Working knowledge of

  Databricks

  for distributed data processing and ML workloads.
• Experience using

  Snowflake

  or similar cloud data warehouses for analytical querying and data modeling.
• Basic understanding of

  data warehousing concepts

  , dimensional modeling, and analytical data models.
• Strong analytical mindset, structured problem-solving skills, and

  excellent stakeholder communication

  abilities.

Certifications (Preferred / Nice to Have)

• Databricks Certified Data Scientist / Machine Learning Professional

• Snowflake SnowPro Core or Advanced Certification

• AWS Certified Machine Learning – Specialty

• Google Professional Data Engineer

• Microsoft Azure Data Scientist Associate

• Any recognized

  Data Science, Machine Learning, or Cloud certification

Good to Have

• Experience with

  deep learning frameworks

  (TensorFlow, PyTorch).
• Exposure to

  cloud platforms

  (AWS, GCP, Azure).
• Hands-on experience with

  big data technologies

  (Spark, Kafka, Hadoop).
• Knowledge of

  MLOps

  , CI/CD pipelines, model deployment, and monitoring.
• Experience working on

  business analytics, KPI tracking, or executive dashboards

  .
• Domain exposure in

  Finance, Retail, Healthcare, Manufacturing, or SaaS

  .
• Prior experience

  mentoring teams or leading data science initiatives

  .