The Robinson Group is searching for a prestigious client of ours creating an new data strategy.
Our client is regularly voted one of the best places to work and strives for great work/life balance.
They have created this new role titled Data Science Manager.
This position will play a key role as you become a leader and team builder in the Data and Insights organization.
Relocation is provided.
This high profile role is well positioned for advancement within the company.
As you grow the team through hiring and talent development, you will work with the other Data and Insights leaders, as well as other data science teams, to define and deliver and maintain critical, data models, forecasting, predictive and prescriptive analytics that drive products, risk profiles, operational efficiencies, customer programs and integrate into our tools, solutions and services.
- Must be able to analyze and establish the cumulative impact of all analytics both over short-term and over long-term periods and align to benefits, cost savings, revenue and ROI.
-Will assist in building a successful deep insights practice that can provide insights into marketing, actuarial sciences, underwriting, claims, product development and call center activities to name a few.
-Provide mentorship and lead data science staff and provide analytical thought leadership and bring cutting edge statistical knowledge to solve complex business problems.
- Develop the analytics to best drive insights across business lines.
- Demonstrated ability to play a leadership role in large, complex analytical projects.
- Develop compelling narratives that connect modeling results with client business problems.
- Provide insights to senior management to support strategic decision-making, preparing and delivering insights and recommendations based on analysis.
- Lead and create a team of data scientists
- Provide POVs and thought leadership on modeling topics
- Provide technical leadership across multiple teams, by understanding a key technology space deeply enough to help guide strategy
- Inspire data science innovations that fuel the growth of the organization
- Provides leadership in advanced engineering, data science and analytics in the development of current or future products, technologies or services.
- Lead a team of data scientists to design, prototype, implement and test predictive and prescriptive analytic models
- Partner with Data Engineers and Project Managers to deliver end-to-end solutions
- Partner with cross-functional teams to identify and explore opportunities for the application of machine learning.
- Applies artificial intelligence and machine learning techniques to solve complex questions or fuel new business opportunities
- Build and/or utilize toolsets and set up processes for extracting information from unstructured data streams.
- Implements data and analytics solutions, through data science techniques, that solve business problems and create business value.
- Provides technical guidance and mentoring to business insight and visualization teams, as needed.
- Leads and executes independent quantitative research projects, leveraging data from multiple sources
- Uses best practices to understand the data and develop statistical, analytical techniques to build models that address business needs.
Required Knowledge and Skills:
- MS or PHD degree preferred in statistics, applied mathematics, or computer science (machine learning)
- 5+ years with predictive modeling techniques and experience in leading predictive modeling initiatives
- 3+ years of management experience
- Ability to break down complex business and technical problems into opportunities for analytical study
- Extensive knowledge and experience in data science, including expertise in one or more of: machine learning, big data/data mining, statistics, business/customer intelligence, data modeling, databases, data warehousing, or a similar field.
- Business application of the following techniques hierarchical Bayesian, Markov chain Monte Carlo, random forests, generalized boosted models, generalized additive models, neural networks, time-series forecasting, game theory, conditional probabilities or other similar approaches
- Deep knowledge of statistical areas such as ANOVA, multiple regression, timeseries modeling, principal component analyses, decision trees, clustering, etc.
- Experience programming in R, SQL, Python
- Automate data wrangling, iterative solution search and operationalization of models, working alongside data architects.
- The ability to handle missing data through an algorithmic approach such as multiple imputations to enable insights in sparse and messy datasets
- Significant experience coding and maintaining predictive algorithms
- Superior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses
- Fluency with analytics platforms like SAS, DSX or SPSS, Data Robot, Alteryx, etc.
- Exceptional troubleshooting skills and thriving in high-expectation scenario with many stakeholders.