Senior Data Scientist – Attrition Models
Fractal Analytics is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.
Please visit Fractal | Intelligence for Imagination for more information about Fractal.
Role Overview:
We are looking for an experienced Senior Data Scientist to build and deploy Attrition Models within the technology sector. Attrition Models will use various data sources like product adoption, voice of customer data, sales touch points, policy/terms sentiment, errors, success plans, etc.
Utilizing strong Python, SQL, and ML modeling expertise, you will work alongside a diverse team of Data Engineers, MLOps Engineers, and Data Scientists to develop and productionalize these Attrition Models and insights. You will create deep insights from raw and aggregated data and deploy models using AWS Sage maker and related AWS services.
Responsibilities:
- Develop and productionalize ML/DL models including Tree-based models (XGB, RF), Linear/Logistic Regression, RNNs, and ANNs.
- Work on supervised ML modeling for regression and classification problems, including handling imbalanced class issues.
- Collaborate with cross-functional teams to deliver insights and deploy models in AWS Sagemaker.
- Create deep insights from scratch using raw and aggregated data.
- Ensure model monitoring and observability post-deployment.
Qualifications:
- 3-5+ years’ experience as a Senior Data Scientist with strong Python, SQL, Snowflake, and ML modeling skills.
- Experience in attrition modeling and productionalizing ML/DL approaches.
- Strong understanding of supervised learning algorithms and imbalanced class handling techniques.
- Experience (nice to have) with Kubernetes orchestration, containerization, and AWS services such as Sagemaker, S3, Lambda, MWAA, and ECR and other deployment related AWS functionalities.
- Experience with version control tools like GIT and visualization tools such as Tableau.
Pay:
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $115,000 to $175,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.
Benefits:
As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a “free time” PTO policy, allowing you the flexibility to take time needed for either sick time or vacation.
Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
