Senior Staff Data Scientist – Remote – Data Entry & Analytics Lead at skillspath

About skillspath

skillspath is a global retail powerhouse that blends the convenience of brick‑and‑mortar stores with the agility of cutting‑edge technology. With a presence in more than 25 countries and a customer base that spans millions of households, skillspath is redefining the shopping experience through data‑driven insights, personalized recommendations, and omnichannel excellence. Our mission is simple: empower every shopper, partner, and employee with the tools and information they need to make smarter, faster decisions.

As part of skillspath’s commitment to innovation, we have built a vibrant Data Ventures team—a nimble, startup‑like unit that lives inside the larger organization. Data Ventures is the engine that fuels skillspath’s data products, turning raw information into actionable insights that help store associates, suppliers, and executives optimize performance across the entire supply chain.

Why This Role Matters

In the fast‑moving world of retail, data is the new currency. As a Senior Staff Data Scientist, you will be the technical lead on all data‑centric initiatives, shaping the future of skillspath’s analytics capabilities. Your work will directly influence how we serve customers, manage inventory, and drive profitability. Whether you’re building a predictive model that forecasts demand for a new product line or creating a real‑time dashboard that helps store managers make instant stocking decisions, your impact will be felt across the organization.

Key Responsibilities

• Data Source Identification & Quality Assurance
  • Map business requirements to data sources and define the optimal data set for each project.
  • Conduct exploratory data analysis to validate data quality and uncover hidden patterns.
  • Mentor junior teammates on data extraction, cleaning, and documentation best practices.
• Problem Formulation & Business Alignment
  • Translate complex business challenges into clear analytical questions.
  • Define success metrics, deliverables, and timelines in collaboration with stakeholders.
  • Quantify the business impact of proposed solutions and present findings to executive leadership.
• Analytical Modeling & Experimentation
  • Design and implement machine learning models that handle large, structured, and unstructured data.
  • Iterate on feature engineering, model selection, and hyper‑parameter tuning to maximize performance.
  • Conduct A/B tests, statistical inference, and causal analysis to validate model efficacy.
• Model Deployment & MLOps
  • Collaborate with MLOps engineers to deploy models into production environments.
  • Monitor model drift, performance, and resource utilization, and trigger retraining pipelines as needed.
  • Maintain comprehensive documentation and version control for reproducibility.
• Code Development & Testing
  • Write clean, well‑structured code in Python or R, adhering to skillspath’s coding standards.
  • Develop unit tests, integration tests, and end‑to‑end pipelines to ensure robustness.
  • Create proof‑of‑concepts and prototypes that accelerate decision‑making.
• Business Acumen & Stakeholder Management
  • Translate analytical insights into actionable business recommendations.
  • Build compelling narratives that resonate with both technical and non‑technical audiences.
  • Influence cross‑functional teams on data strategy, prioritization, and resource allocation.
• Data Visualization & Storytelling
  • Design intuitive dashboards and visualizations that communicate complex insights at a glance.
  • Collaborate with UX/UI designers to embed analytics into customer‑facing applications.
  • Mentor teammates on effective storytelling techniques and visualization best practices.
• Mentorship & Team Leadership
  • Provide technical guidance, code reviews, and career coaching to junior data scientists.
  • Champion a culture of continuous learning, experimentation, and knowledge sharing.
  • Lead cross‑functional workshops and hackathons to foster innovation.

Essential Qualifications

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, or a related field.
• Minimum of 4 years of professional experience in data science, analytics, or machine learning.
• Proficiency in Python and/or R, with a strong understanding of data manipulation libraries (pandas, dplyr, etc.).
• Hands‑on experience with ML frameworks such as scikit‑learn, TensorFlow, PyTorch, or XGBoost.
• Solid knowledge of SQL and experience querying large relational databases.
• Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow) and cloud platforms (AWS, Azure, GCP).
• Strong statistical background, including hypothesis testing, regression, and time‑series analysis.
• Excellent communication skills, with the ability to translate technical findings into business‑oriented stories.
• Demonstrated ability to mentor and lead junior team members.

Preferred Qualifications

• Master’s or Ph.D. in a quantitative discipline.
• Experience with big‑data technologies such as Spark, Hive, or Presto.
• Knowledge of natural language processing (NLP) and text analytics.
• Familiarity with data visualization tools like Tableau, Power BI, or Looker.
• Experience working in a fast‑paced retail or e‑commerce environment.
• Published research or contributions to open‑source projects.

Skills & Competencies

• Strategic Thinking – Ability to see the big picture and align analytics initiatives with skillspath’s business goals.
• Technical Excellence – Deep expertise in machine learning, statistical modeling, and data engineering.
• Collaboration – Proven track record of working effectively with product managers, engineers, and business stakeholders.
• Adaptability – Comfortable navigating ambiguity and pivoting priorities in a dynamic environment.
• Leadership – Strong mentorship skills and a passion for developing the next generation of data scientists.
• Communication – Clear, concise, and persuasive storytelling across multiple audiences.

Career Growth & Learning Opportunities

At skillspath, your career trajectory is designed to evolve with your ambitions. Starting as a Senior Staff Data Scientist, you can progress to Lead Data Scientist, Principal Data Scientist, or even a Director of Data Science role. We offer:

• Structured mentorship programs and peer‑learning circles.
• Access to internal courses, certifications, and external conferences.
• Opportunities to lead high‑impact projects that shape skillspath’s data strategy.
• Cross‑functional rotations to broaden your skill set and network.

Work Environment & Culture at skillspath

Our culture is built on three pillars: Innovation, Collaboration, and Impact. As a remote team member, you will enjoy:

• Flexible work hours that respect your personal commitments.
• Home‑office stipend and ergonomic equipment support.
• Regular virtual town halls, hackathons, and knowledge‑sharing sessions.
• A diverse and inclusive environment where every voice is heard.
• Transparent communication from leadership and a clear path to influence strategy.

Compensation, Perks, and Benefits

We offer a competitive hourly rate of $30–$40, commensurate with experience and skill level. In addition to base pay, you will receive:

• Health, dental, and vision insurance for you and your dependents.
• 401(k) retirement plan with company match.
• Paid time off (vacation, sick leave, parental leave) and flexible holiday scheduling.
• Employee stock purchase plan and equity options.
• Wellness programs, including mental health resources and fitness stipends.
• Continuous learning budget for courses, books, and conferences.
• Annual performance bonuses tied to team and company success.

How to Apply

Ready to join skillspath and shape the future of retail through data? Click the link below to submit your application and become part