As a Sr. Data Scientist, you will leverage advanced analytics, machine learning, and large-scale data modeling to drive strategic business decisions. You will work closely with cross-functional teams, translating complex data into actionable insights that influence growth and operational efficiency. This role combines hands-on model development with strategic analysis, requiring expertise in predictive modeling, LLM deployment, and visualization. You will be responsible for ensuring data quality, monitoring model performance, and communicating findings clearly to technical and non-technical stakeholders. The environment is dynamic, collaborative, and fast-paced, ideal for candidates passionate about applying data science to solve impactful business problems.

Accountabilities:

In this role, your key responsibilities will include:

Develop, enhance, and productionize machine learning models, including LLM-powered solutions such as summarization, information extraction, and classification
Conduct deep-dive analyses to identify variance drivers and support business decisions
Design, create, and maintain dashboards and visualizations to communicate insights effectively
Perform exploratory data analysis and ensure high-quality, clean, and structured datasets
Monitor model performance, detect drift, and implement rigorous testing to ensure reliability
Collaborate with product, engineering, and business teams to translate requirements into data-driven solutions
Communicate complex data findings to non-technical stakeholders, providing actionable recommendations

Requirements

The ideal candidate should bring:

6+ years of experience in data science or analytics roles, with at least 3+ years focused on machine learning and modeling
Strong programming proficiency in Python and PySpark for modeling, data analysis, and machine learning
Advanced SQL skills and experience handling large, semi-structured datasets
Familiarity with ML frameworks and libraries, including pandas, NumPy, seaborn, matplotlib, MLFlow, scikit-learn, TensorFlow, and PyTorch
Hands-on experience fine-tuning, prompt engineering, and deploying LLMs in production
Expertise in predictive modeling, statistical analysis, and experimental design (A/B testing, regression, hypothesis testing)
Strong communication, collaboration, and problem-solving skills, with the ability to translate technical results into actionable insights

Preferred Skills:

Experience with visualization tools such as Tableau or PowerBI
Familiarity with data lakes, Databricks, and version control systems like Git
Availability to work in Eastern or Central U.S. time zones

Benefits

This role offers a comprehensive and competitive package, including:

Base salary range: $115,000 - $125,000
Annual bonus: 10% of earnings
Health, dental, and vision insurance
401(k) plan with company match
Paid time off and flexible work arrangements
Opportunity to work with large-scale, cutting-edge analytics projects
Exposure to advanced machine learning and LLM technologies
Collaborative and dynamic work environment

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience and achievements.

📊 It compares your profile to the job's core requirements and past success factors to determine your match score.

🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.

🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!