We are looking for a mid- to senior-level Data Scientist that can combine data science with deep knowledge and understanding of machine learning and big data technologies to create and evaluate novel solutions. The candidate will spearhead the development of new products and be able to go from POC to production. Candidate will work with a broad range of interesting and proprietary data as part of a diverse development team. The ideal candidate will have strong collaboration skills to identify and gather relevant data from functional users.
In this role you will:
- Develop and validate statistical and machine learning models to identify trends within structured, semi-structured and time-series data; all heavily leveraging the existing big data infrastructure, making use of leading edge analytical approaches
- You will be expected to take complex datasets, mashup models, and solve complex problems with predictive techniques
- At least 4+ years professional work experience as a Data Scientist/Data Engineer
- Solid fundamentals, machine learning concepts, regression, clustering, Bayesian modeling, probability theory, stats
- Expertise with database systems, SQL/NOSQL, and columnar databases are mandatory
- Fluent in Python
- Experienced with parallelization tools Hadoop/Spark
- Experienced in turning functional requirements into technical methods
- Experienced with cloud services and cloud computing – tools and ML
- Exceptional analytical, mathematical and problem solving skills
- 3+ years of progressive experience building statistical and machine learning models
- Candidates must have a strong understanding of financial markets. Must have working experience with multiple algorithms and knowledge to pick the right algorithm for a given business problem.
- A strong math and computer science background are key. Working experience with Databricks, AWS Sagemaker, and SQL preferred.
- Experience developing ML classification, regression models using Python and/or Scala
- Experience working with structured, semi-structured, and time-series data to build models
- Ability to translate complex mathematical results and findings for executive audience
- Ability to work in a highly collaborative manner with a reasonable degree of independence
- Ability to effectively manage time to handle competing high priority projects
Essential Duties and Responsibilities
- Proven track record in the areas of artificial intelligence, machine learning, NLP. Should have good experience building solutions in the area of data-science for large enterprises.
- Should be well versed with python statistical modeling, data analytics.
- Define how analytics solution will be constructed: which existing data will be leveraged, how they will be integrated, and engineered, and how gaps need to be filled.
- Extract, merge, clean, and normalize large-scale data from disparate sources in preparation for exploratory data analysis, model building and validation – within a big data environment.
- Develop, validate ML classification, regression models using Python or similar in order to directly answer business needs, and to positively impact business operations.
- Prepare appropriate data visualizations and presentations to highlight findings and recommendations for both a technical and executive audience.
- Promote a unified approach leveraging existing data sets and efforts while also ensuring collaboration throughout the organization to ensure adoption and common standard approach
- Establish credibility as a trusted advisor to key stakeholders across the enterprise in order to drive business actions and outcomes based on results of your analysis
- Apply good business and financial acumen to create and assess business cases
- Implement appropriate mechanisms to track, measure the business impact of your work
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.