Associate Director, Data Science at Blend360

Columbia, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

14 May, 26

Salary

0.0

Posted On

13 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Predictive Modelling, Statistical Analysis, Text Mining, Geo-spatial Analytics, Time Series Forecasting, Optimization, Python, R, SQL, Spark, Tableau, Power BI, AWS, Azure

Industry

Professional Services

Description

Company Description About Blend360: Blend360 is a premier AI services provider, committed to co-creating meaningful impact for our clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, we tackle significant challenges by seamlessly aligning human expertise with artificial intelligence. We are dedicated to unlocking value and fostering innovation for our clients by harnessing world-class talent and data-driven strategies. We believe that the power of people and AI can have a transformative impact on the world, creating more fulfilling work and innovative solutions for our people and clients. Job Description We are looking for someone who is passionate about managing the successful delivery of machine learning models, algorithms to solve clients’ business problems (mainly in sales & marketing use cases); someone who has advanced data science subject matter expertise that can help our clients to evaluate different sources of data, discover patterns hidden within raw data, create insights, and develop recommendations to impact clients business outcome. Main Responsibilities: Use data to provide recommendations for the products and services that best fit individual customers, along with the associated value proposition Work with team leaders to get client input & feedback, translate clients business problem into a solvable Data Science exercise, formulate different approaches, outline pros and cons for each approach, get alignment on approaches, deliverables, and overall timeline with clients. Work closely with analytic teams to develop complex algorithms and statistical predictive models to evaluate scenarios and potential future outcomes; leverage problem solving / analytical skills, quantitative expertise, programming and data analysis to identify potential risks related to existing portfolios as well as new products and develop methodologies for tracking and reporting them Perform analyses of structured and unstructured data to solve multiple and complex business problems utilizing advanced data science and machine learning techniques and specialized industry expertise and develop analyses and models based on complex energy market indicators and cost components Applies analytical rigor & statistical methods to analyze large amounts of data, using advanced statistical techniques Manage large & complex analytical projects: data exploration, model building, performance evaluation & testing Collaborate w/business partners to develop technical/business approaches and new/enhanced technical tools Interacts with internal and external peers and management to share highly complex information related to areas of expertise and/or to gain acceptance of new or enhanced technology / business solutions Qualifications MS or PhD degree in quantitative studies, such as Statistics, Math, Operation Research, Economics, Advanced Analytics, Computer Science, Engineering Strong quantitative and analytics background, including advanced-level skillset in predictive modelling, statistical analysis, machine learning, text mining, geo-spatial analytics, time series forecasting, optimization. 8-10 years’ professional experience working in FiServ, Insurance, Hospitality and Retail industries on applying data science and analytics in sales and marketing applications. Familiarity with digital marketing ecosystem. Extensive experience in email marketing, digital marketing, and call center analytics and direct marketing are preferred. Experience with one or more Advanced Data Science software languages (Python, R) Experience with structured or un-structured data analysis and tools (SQL, Spark, Tableau, Power BI tools) Experience with cloud-based platforms (AWS, Azure, Google) Demonstrated ability to communicate technical ideas and results to non-technical clients in written and verbal form Strong organizational, management and leadership skills. Experience managing and mentoring junior resources across different geo-locations.

Responsibilities

The role involves managing the successful delivery of machine learning models and algorithms to solve client business problems, primarily in sales and marketing use cases. Responsibilities include translating business problems into solvable Data Science exercises, developing complex predictive models, and applying analytical rigor to large datasets.