Senior Data Scientist

Job Summary

We are seeking a Senior Data Scientist to lead the design and implementation of advanced analytics and data science solutions. This role requires a strong foundation in statistics, machine learning, data engineering, and domain-driven problem solving. The ideal candidate will have experience building end-to-end data science solutions, from exploratory data analysis and feature engineering to production-ready-models and business insights. You will collaborate closely with engineers, analysts, and business stakeholders to drive measurable outcomes.

Key Responsibilities

 Design, build, and evaluate predictive and prescriptive models (regression, classification, forecasting, clustering, recommendation systems).

 Apply advanced ML methods (gradient boosting, ensemble models, transformers for tabular/text, probabilistic models).

 Conduct A/B tests and causal inference to measure business impact.

 Perform exploratory data analysis (EDA) using statistical and visualization tools.

 Translate data findings into actionable insights with clear storytelling for non-technical audiences.

 Build dashboards and reports to support decision-making.

 Work with SQL, Spark, Dask, or BigQuery to process and transform large datasets.

 Collaborate with data engineers to ensure high-quality, reliable data pipelines.

 Apply feature engineering, data augmentation, and missing data handling strategies.

 Contribute to model deployment using MLflow, SageMaker, Vertex AI, or Azure ML.

 Support model monitoring and retraining strategies.

 Use Python (Pandas, NumPy, Scikit-learn, Statsmodels, PyTorch/TensorFlow), R, SQL,

and Jupyter for analysis and modeling.

 Use visualization & BI tools (Matplotlib, Seaborn, Plotly, Power BI, Tableau, Looker).

 Track experiments with MLflow, DVC, or Weights & Biases.

 Partner with product managers and business teams to frame problems and define

success metrics.

 Mentor junior data scientists and analysts.

 Champion data-driven decision-making across the organization.

Required Qualifications & Skills

 Strong programming skills in Python and SQL; familiarity with R or Julia is a plus.

 Solid foundation in statistics, probability, linear algebra, and hypothesis testing.

 Experience with machine learning techniques (supervised/unsupervised learning,

ensembles, time series).

 Proficiency with data visualization and ability to communicate insights effectively.

 Hands-on experience with big data tools (Spark, Dask, BigQuery).

 Cloud experience with AWS, GCP, or Azure for data science workflows.

 Familiarity with version control (Git), experiment tracking, and reproducible

workflows.

 Excellent communication, collaboration, and problem-solving skills.

 Proven ability to mentor junior engineers and lead initiatives.

Preferred Qualifications

 Domain expertise in manufacturing, healthcare, retail, or e-commerce applications.

 Experience with NLP or computer vision applied to data-rich use cases.

 Hands-on experience with causal inference, Bayesian methods, or reinforcement

learning for experimentation.

 Prior open-source contributions, publications, or patents.

 Experience with BI/analytics strategy and executive-level presentations.

Education & Experience

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• PhD or strong research experience is a plus, but not required.
• 5–7+ years of professional experience in data science or advanced analytics, with evidence of driving business impact.

What We Offer

 High-impact data science projects that solve real-world problems.

 Continuous learning opportunities with cloud credits, courses, and conference sponsorships.

 Competitive salary, benefits, and performance-based incentives.

 Flexible hybrid/remote working environment.

 A culture of collaboration, innovation, and knowledge sharing.

Job Type: Full-time

Pay: Rs450,000.00 - Rs600,000.00 per month

Experience:

• Relevant: 5 years (Required)

Location:

• Lahore (Preferred)

Work Location: In person