Job Description

Nisum is a leading global digital commerce firm headquartered in California, with services spanning digital strategy and transformation, insights and analytics, blockchain, business agility, and custom software development. Founded in 2000 with the customer-centric motto "Building Success Together," Nisum has grown to over 1,800 professionals across the United States, Chile, Colombia, India, Pakistan, and Canada. A preferred advisor to leading Fortune 500 brands, Nisum enables clients to achieve direct business growth by building the advanced technology they need to reach end customers in today’s world, with immersive and seamless experiences across digital and physical channels.

What You'll Do

This is an exciting opportunity for an experienced Data Scientist to leverage advanced data analysis, feature engineering, and visualization to derive actionable insights. You will work on solving complex business problems using data-driven approaches, statistical techniques, and scalable machine learning models. Your work will directly contribute to enhancing operational efficiency, customer engagement, and product innovation.

Exploratory Data Analysis & Visualization

• Perform detailed data analysis using pandas, numpy, sweetviz, pandas-profiling, and plotly.
• Identify trends, detect outliers, and address missing values using statistical summaries and visualizations with seaborn, matplotlib, and plotly.
• Create automated EDA reports to support data-driven decision-making.
  
  

Feature Engineering & Selection

• Develop and apply robust feature engineering techniques such as encoding (one-hot, label, ordinal), TF-IDF, and domain-specific transformations.
• Engineer features from time-series datasets using lags, rolling statistics, and seasonal patterns.
• Apply dimensionality reduction and feature selection techniques to optimize model performance and interpretability.
  
  

Model Support & Optimization

• Collaborate with ML engineers to transform features into model-ready datasets.
• Contribute to model pipeline enhancements by integrating engineered features and tracking their impact using A/B testing or evaluation metrics.
• Work with multiple teams to ensure smooth feature integration and high-quality output.
  
  

What You Know

• Strong programming skills in Python with experience in data science libraries such as pandas, numpy, scikit-learn, and plotly.
• Deep expertise in data visualization, statistical analysis, and report generation using seaborn, matplotlib, sweetviz, and pandas-profiling.
• Proven experience with feature engineering for structured, unstructured, and time-series data.
• Familiarity with text feature extraction (e.g., TF-IDF, embeddings) and dimensionality reduction techniques (e.g., PCA, t-SNE).
• Understanding of model lifecycle and contribution of engineered features to performance.
• Experience with collaborative tools such as Git, Jupyter, and Agile workflows.
  
  

Additional Requirements

• Strong problem-solving and analytical thinking skills.
• Excellent communication abilities for presenting data-driven insights to both technical and non-technical audiences.
• Ability to work independently as well as collaboratively across data, product, and engineering teams.
• Self-motivated, detail-oriented, and curious about finding patterns in data.
  
  

Education

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
  
  

Benefits

In addition to competitive salaries and benefits packages, Nisum offers its employees some unique and fun extras:

• Health Benefits: Comprehensive health coverage, including in-patient, out-patient care, and life insurance.
• Work-Life Balance: Flexible paid time off for medical leave, pilgrimage, family planning, and personal time.
• Incentives & Rewards: Financial rewards, interest-free loans, extra salary, car financing, and savings programs.
• Development & Training: Structured training, study sponsorships, international trips, and appreciation programs.
• Corporate Appliances: Essential work tools, including a laptop, internet device, and accessories.
• Office Facilities: Gym, gaming room, free lunches, and a vibrant work environment.