At Ameritas, fulfilling life is what we do daily. We continuously strive to help our customers and employees enjoy life at its very best by reducing uncertainty, helping grow assets and protecting what is most cherished. We're here to help people put worry behind and the future ahead and help enable a life that's rich in family, happiness, health and financial security. When lives are fulfilled, our mission is fulfilled.
Ameritas Life Insurance Corp is seeking a Data Science Manager to become a leader in the Data and Insights organization at Ameritas and build our data science team. 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.
This individual must also 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. The Senior Data Science Manager will report into the VP of Data and Insights and 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. The Senior Data Science Manager is expected to provide mentorship and lead data science staff and provide analytical thought leadership to Ameritas and bring cutting edge statistical knowledge to solve complex business problems. The individual is also expected to provide good technical skills, have the ability to continuously learn from industry and academic work, and have strong communication skills.
This role will be an important key to Ameritas technology enablement. As a key contributor to Ameritas Information Technology department, the Senior Data Science Manager role is defined as follows:
Develop the analytics to best drive insights across the Ameritas 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 Ameritas as a whole
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.
Required Interpersonal Skills:
The skill of presenting complicated data in a way that allows the audience to focus on the underlying trends and insights
Explain complex modeling approaches in layman's terms and discuss modeling results and business case impact with non-technical business users.
Ability to extract insights to identify growth opportunities and effectively communicate outcomes and recommendations
Enthusiasm for learning the practical application of statistical analysis to address business issues.
Strong sense of ownership, relentless curiosity, and self-driven approach to problem solving.
Established professional communication, presentation, and influencing skills
Strong organizational and project management skills, to ensure you can keep on top of your own and others workload
Lead effective data analysis that may suggest risk or opportunities for client.
Partnership/collaboration with marketing business partners and other enterprise teams.