TenViz Predictive Analytics

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

2+ years in B2B marketing
Experience working with international or enterprise clients is a plus
Comfortable explaining complex products in simple terms
Hands-on with LinkedIn outreach, email campaigns, or content
Familiar with CRM tools (HubSpot, Salesforce, etc.)
Able to track results and adjust campaigns based on data
Strong written English

Nice to have:
FinTech or data/analytics background
Basic understanding of financial markets
Experience with ads, SEO, or marketing automation

What You’ll Do

Run B2B marketing campaigns (mostly LinkedIn and email)
Find and engage potential clients
Create simple content (posts, emails, decks)
Work closely with sales on leads and messaging
Track what works and improve it

Example projects

LinkedIn outreach to investors and funds
Email campaigns for lead generation
Content explaining how our product is used
Supporting product launches

What You Get

Remote work, flexible schedule
Paid vacation (after 8 months)
Learning opportunities in FinTech and marketing
Small team, no micromanagement
Work with global clients

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