TenViz Predictive Analytics

Remote – Full-time – Flexible Hours - Shifted schedule to EST (New York) timezone

About TenViz

TenViz Predictive Analytics builds AI-powered solutions that help Fortune 100 investors anticipate market shifts before they become consensus. We combine financial expertise, mathematical rigor, and AI research to deliver predictive analytics for institutional investors.

Your Expertise

• Strong interest in quantitative and algorithmic approaches
• BSc/MSc in Math, Physics or related field with solid background in statistics, linear algebra and probability theory
• Advanced Linear Algebra, Advanced Statistics, Using Linear Algebra methods in Statistical analysis
• 2+ years in data research, quantitative modeling, ML prototyping, and backtesting
• Skilled in Python, SQL, Git
• Experience with  experiment tracking, pipeline orchestration and workflow automation

Nice to have:

• Bayesian inference, reinforcement learning, or ensemble methods
• Financial econometrics, time-series forecasting, or regime modeling

What You’ll Do

• Design predictive models using probabilistic, ML, and hybrid approaches
• Analyze large-scale financial datasets to detect hidden patterns and early regime shifts
• Prototype and evaluate algorithms, from deep learning to Bayesian models
• Write production-grade research code in Python/SQL that integrates into pipelines
• Translate results into insights and themes investors can act on — not just outputs

Example projects:

• Forecasting inflation via commodity price signals
• Constructing probabilistic forecasts of currency moves around macroeconomic announcements
• Designing a Bayesian model to estimate recession probabilities from yield curve dynamics
• Designing a regime-aware ML pipeline that switches models depending on market conditions
• Creating hybrid ensembles that outperform traditional benchmarks

What’s in It for You

• Remote-first, flexible hours
• Paid vacation & holidays (after 8 months)
• Continuous learning: advanced ML/DL workshops, probabilistic methods, optimization
• Supportive, collaborative team — no micromanagement, focus on trust and creativity
• Work on real financial problems where your models influence billion-dollar decisions

PERSONALITY & SKILLS:

- natural team player, ready to go the extra mile to help a colleague

- very detail-oriented

- proactive and self-organized, excited to improve and automate existing sales and marketing processes

- fast learner

- fluency in English

- advanced computer skills (user)

DUTIES:

- Proactively reaching out to new leads

- Handle responses, scheduling initial and follow-up calls

- Create & analyze marketing campaigns

- Matching existing timely ideas with client's needs and proactively ensuring that clients are updated

- Invoicing and tracking receivables for existing clients

- Prioritizing sales & marketing efforts for the team

- Updating marketing and sales presentations

- Working hours are shifted to the US (afternoon and evening hours in Ukraine) & working remotely

DUTIES AND RESPONSIBILITIES
- Design, build, and maintain ETL/ELT pipelines to collect, process end-to-end, and store financial data
- Write optimized, efficient code to process and analyze financial data
- Design and evolve the database schema; write and tune queries
- Build and maintain integrations with external data sources and APIs (market data feeds, vendor APIs, cloud storage)
- Identify and resolve performance bottlenecks
REQUIRED QUALIFICATIONS AND EXPERIENCE
- 1–2+ years designing and maintaining data pipelines, databases (SQL / PostgreSQL), and ETL processes
- Python with Pandas / NumPy and Git
- Comfortable working with cloud object storage — AWS S3 or GCP Cloud Storage (GCS)
- A solid understanding of or interest in financial data, instruments, and markets
- Intermediate English
NICE TO HAVE — BONUS, NOT EXPECTED
- Workflow orchestration: Airflow, Dagster, or Prefect
- Columnar / interchange formats: Parquet, Arrow, DuckDB
- Streaming or real-time feeds: Kafka, WebSocket market data
- Financial protocols / vendor APIs: FIX, Polygon, Refinitiv, Bloomberg
- Time-series databases: TimescaleDB, ClickHouse
- dbt, Docker, CI/CD
- Model Context Protocol (MCP) for AI/agent integrations
- Familiarity with R
- Background in Computer Science, Physics, or Applied Mathematics
WORK ENVIRONMENT
- Remote
- Flexible hours, 8 am – 8 pm
- Compassionate teammates and real growth opportunities
SALARY AND BENEFITS
- Paid vacation and state holidays (available to request after 8 months)
- Workshops and skills-boost courses encouraged