About
Data science is a long-term investment that requires strong leadership, quality hiring, and
tailored development. Whether you’re just starting out or have a team in place already,
deficiencies in any of these areas will seriously impede your business growth.
d2l is a team of data professionals offering hands-on guidance for tackling your next data
science challenge. Consulting is successful when there is a swift data discovery period, flexible
scope, and clear success metrics. We value the consistent mentorship and training that is
required to optimize the return on your investment. We’re building partnerships, not short-term
revenue.
Services
Why do you need consulting? ‘KUBA’:
- Knowledge – lack of internal experience to tackle the next big challenge
- Urgency – hiring and on-ramping takes time, you can’t “hit the ground running”
- Budget – have money allocated and can pay a premium
- Availability – competition and location has you at a disadvantage for attracting top talent for full time positions
Data Discovery
- Effective data science starts with a deep understanding of the data – including its shortcomings. We approach data discovery with a surgical precision to quickly extract key insights.
Strategy
- A pragmatic and focused strategy is vital to making data-driven decisions, as well as the flexibility to adapt to an ever-changing competitive climate. We collect and synthesize stakeholder requirements and KPIs to ensure concise strategy execution.
Development
- Development is a known point of divergence between expectation and implementation. We foster accountability and consistent communication from our developers to safeguard against all too common delays and revisions.
Training
- We want to cultivate evolving partnerships, not dependencies. We end engagements with comprehensive training to leave your team self-sufficient, and ready to take on the next challenge.
Areas of Expertise
Business Intelligence
- Industry experts on reporting tools to match your specific needs. Infrastructure and tools must work in harmony to keep pace with the competition
Modeling
- The earlier you know the predictive capability of your data the better. Experience matters in building solutions, not just identifying setbacks
Inference
- Requires the proper tool to make accurate data-driven decisions. Understanding your assumptions and drawing the correct conclusions is critical in measurement solutions
Project Management
- Data science projects require multiple teams and touch points. The necessary flexibility in scope requires an effective communicator and negotiator
Industries
- adtech, automotive, cannabis, cpg, energy, financial services, media & entertainment, retail, transportation, real estate
