Senior Data Scientist

We are looking for an experienced Senior Data Scientist who can lead the development and implementation of advanced data science solutions to tackle complex business challenges. You will play a key role in shaping data-driven strategies, optimizing revenue streams, and delivering actionable insights across the organization. If you are passionate about leveraging data to drive impact and thrive in a collaborative, fast-paced environment, we’d love to meet you.

Job Title: Senior Data Scientist

We are looking for an experienced Senior Data Scientist who can lead the development and implementation of advanced data science solutions to tackle complex business challenges. You will play a key role in shaping data-driven strategies, optimizing revenue streams, and delivering actionable insights across the organization. If you are passionate about leveraging data to drive impact and thrive in a collaborative, fast-paced environment, we’d love to meet you.

Key Responsibilities

Advanced Data Science & Modeling

• Lead the development, evaluation, and deployment of sophisticated statistical and machine learning models to drive critical business decisions and optimize major revenue streams.

• Design, oversee, and review complex experiments (A/B testing, multivariate experiments, causal inference) to assess the impact of product, growth, and marketing strategies.

• Conduct advanced exploratory data analysis (EDA) to surface actionable insights, strategic opportunities, and business risks.

• Establish frameworks and best practices for continuous model performance monitoring, retraining, and lifecycle management.

Leadership & Strategy

• Act as a trusted thought partner to executive stakeholders, translating business challenges into high-impact data science initiatives and communicating sophisticated findings with clarity.

• Mentor and guide junior data scientists and analysts, fostering a culture of rigor, transparency, and innovation within the data team.

• Champion data-driven decision-making and advocate for advanced analytics capabilities across the organization.

Collaboration & Delivery

• Collaborate cross-functionally with machine learning, MLOps, and data engineering teams to productionize models and ensure robust, scalable deployment.

• Define and refine success metrics, business KPIs, and modeling objectives in partnership with product, growth, and operations stakeholders.

• Drive documentation standards for methodologies, model development, and business recommendations to ensure reproducibility and knowledge sharing.

Technical Excellence

• Use and advocate best practices with the Python data science stack (Pandas, NumPy, Scikit-learn, XGBoost, etc.), ensuring reproducibility, code quality, and scalability.

• Leverage modern data infrastructure (AWS Redshift, S3, Glue, Lambda, SageMaker) for data warehousing, ETL, and model deployment.

• Utilize MLflow (or similar) for experiment tracking and model management, and dashboarding tools (Tableau, Power BI, or similar) for analytical storytelling.

Job Requirements

• M.S. or Ph.D. in data science, statistics, mathematics, computer science, economics, or a related quantitative field.

• 5+ years of experience leveraging data science and machine learning in business environments, with a proven track record of delivering impactful models and insights at scale.

• Deep understanding of statistics, probability, experimental and causal inference methods.

• Advanced proficiency in Python, SQL, and collaborative workflows (Git), with demonstrated experience architecting robust data analyses and machine learning pipelines.

• Experience designing, building, and deploying supervised and unsupervised models (regression, classification, clustering, time series forecasting) for production use.

• Exceptional analytical skills, with the ability to simplify and communicate complex technical concepts to diverse audiences, including executive leadership.

• Demonstrated leadership in mentoring junior team members and driving cross-functional collaboration.

Nice to Have

• Deep experience with AWS big data ecosystem (Glue, Lambda, SageMaker) and scalable model deployments.

• Track record of optimizing digital marketing through web analytics (Google Analytics, GetStat, Clicky) and experimentation (A/B testing, multi-armed bandits).

• Exposure to M&A data mining, financial modeling, or advanced risk analytics within large organizations or consulting environments.

Benefits

• Opportunity to lead and shape high-impact data initiatives across the business.

• Collaborative and innovative environment focused on professional growth.

• Work with cutting-edge technology in a high-performance, data-driven team.